{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据分析\n",
    "\n",
    "数据分析的价值主要在于熟悉了解整个数据集的基本情况包括每个文件里有哪些数据，具体的文件中的每个字段表示什么实际含义，以及数据集中特征之间的相关性，在推荐场景下主要就是分析用户本身的基本属性，文章基本属性，以及用户和文章交互的一些分布，这些都有利于后面的召回策略的选择，以及特征工程。\n",
    "\n",
    "**建议：当特征工程和模型调参已经很难继续上分了，可以回来在重新从新的角度去分析这些数据，或许可以找到上分的灵感**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:13:59.322486Z",
     "start_time": "2020-11-13T15:13:55.601445Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "plt.rc('font', family='SimHei', size=13)\n",
    "\n",
    "import os,gc,re,warnings,sys\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:14:18.918041Z",
     "start_time": "2020-11-13T15:14:02.568798Z"
    }
   },
   "outputs": [],
   "source": [
    "path = './data_raw/'\n",
    "\n",
    "#####train\n",
    "trn_click = pd.read_csv(path+'train_click_log.csv')\n",
    "#trn_click = pd.read_csv(path+'train_click_log.csv', names=['user_id','item_id','click_time','click_environment','click_deviceGroup','click_os','click_country','click_region','click_referrer_type'])\n",
    "item_df = pd.read_csv(path+'articles.csv')\n",
    "item_df = item_df.rename(columns={'article_id': 'click_article_id'})  #重命名，方便后续match\n",
    "item_emb_df = pd.read_csv(path+'articles_emb.csv')\n",
    "\n",
    "#####test\n",
    "tst_click = pd.read_csv(path+'testA_click_log.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据预处理\n",
    "计算用户点击rank和点击次数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:14:31.746748Z",
     "start_time": "2020-11-13T15:14:31.409643Z"
    }
   },
   "outputs": [],
   "source": [
    "# 对每个用户的点击时间戳进行排序\n",
    "trn_click['rank'] = trn_click.groupby(['user_id'])['click_timestamp'].rank(ascending=False).astype(int)\n",
    "tst_click['rank'] = tst_click.groupby(['user_id'])['click_timestamp'].rank(ascending=False).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:15:04.503079Z",
     "start_time": "2020-11-13T15:15:04.394329Z"
    }
   },
   "outputs": [],
   "source": [
    "#计算用户点击文章的次数，并添加新的一列count\n",
    "trn_click['click_cnts'] = trn_click.groupby(['user_id'])['click_timestamp'].transform('count')\n",
    "tst_click['click_cnts'] = tst_click.groupby(['user_id'])['click_timestamp'].transform('count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据浏览"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 用户点击日志文件_训练集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:16:07.764776Z",
     "start_time": "2020-11-13T15:16:07.536342Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>click_article_id</th>\n",
       "      <th>click_timestamp</th>\n",
       "      <th>click_environment</th>\n",
       "      <th>click_deviceGroup</th>\n",
       "      <th>click_os</th>\n",
       "      <th>click_country</th>\n",
       "      <th>click_region</th>\n",
       "      <th>click_referrer_type</th>\n",
       "      <th>rank</th>\n",
       "      <th>click_cnts</th>\n",
       "      <th>category_id</th>\n",
       "      <th>created_at_ts</th>\n",
       "      <th>words_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>199999</td>\n",
       "      <td>160417</td>\n",
       "      <td>1507029570190</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>281</td>\n",
       "      <td>1506942089000</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>199999</td>\n",
       "      <td>5408</td>\n",
       "      <td>1507029571478</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>1506994257000</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>199999</td>\n",
       "      <td>50823</td>\n",
       "      <td>1507029601478</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>99</td>\n",
       "      <td>1507013614000</td>\n",
       "      <td>213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>199998</td>\n",
       "      <td>157770</td>\n",
       "      <td>1507029532200</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>5</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>281</td>\n",
       "      <td>1506983935000</td>\n",
       "      <td>201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>199998</td>\n",
       "      <td>96613</td>\n",
       "      <td>1507029671831</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>5</td>\n",
       "      <td>39</td>\n",
       "      <td>40</td>\n",
       "      <td>209</td>\n",
       "      <td>1506938444000</td>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  click_article_id  click_timestamp  click_environment  \\\n",
       "0   199999            160417    1507029570190                  4   \n",
       "1   199999              5408    1507029571478                  4   \n",
       "2   199999             50823    1507029601478                  4   \n",
       "3   199998            157770    1507029532200                  4   \n",
       "4   199998             96613    1507029671831                  4   \n",
       "\n",
       "   click_deviceGroup  click_os  click_country  click_region  \\\n",
       "0                  1        17              1            13   \n",
       "1                  1        17              1            13   \n",
       "2                  1        17              1            13   \n",
       "3                  1        17              1            25   \n",
       "4                  1        17              1            25   \n",
       "\n",
       "   click_referrer_type  rank  click_cnts  category_id  created_at_ts  \\\n",
       "0                    1    11          11          281  1506942089000   \n",
       "1                    1    10          11            4  1506994257000   \n",
       "2                    1     9          11           99  1507013614000   \n",
       "3                    5    40          40          281  1506983935000   \n",
       "4                    5    39          40          209  1506938444000   \n",
       "\n",
       "   words_count  \n",
       "0          173  \n",
       "1          118  \n",
       "2          213  \n",
       "3          201  \n",
       "4          185  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trn_click = trn_click.merge(item_df, how='left', on=['click_article_id'])\n",
    "trn_click.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### train_click_log.csv文件数据中每个字段的含义\n",
    "\n",
    "1. user_id: 用户的唯一标识\n",
    "2. click_article_id: 用户点击的文章唯一标识\n",
    "3. click_timestamp: 用户点击文章时的时间戳\n",
    "4. click_environment: 用户点击文章的环境\n",
    "5. click_deviceGroup: 用户点击文章的设备组\n",
    "6. click_os: 用户点击文章时的操作系统\n",
    "7. click_country: 用户点击文章时的所在的国家\n",
    "8. click_region: 用户点击文章时所在的区域\n",
    "9. click_referrer_type: 用户点击文章时，文章的来源"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:16:18.536902Z",
     "start_time": "2020-11-13T15:16:18.424203Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1112623 entries, 0 to 1112622\n",
      "Data columns (total 14 columns):\n",
      " #   Column               Non-Null Count    Dtype\n",
      "---  ------               --------------    -----\n",
      " 0   user_id              1112623 non-null  int64\n",
      " 1   click_article_id     1112623 non-null  int64\n",
      " 2   click_timestamp      1112623 non-null  int64\n",
      " 3   click_environment    1112623 non-null  int64\n",
      " 4   click_deviceGroup    1112623 non-null  int64\n",
      " 5   click_os             1112623 non-null  int64\n",
      " 6   click_country        1112623 non-null  int64\n",
      " 7   click_region         1112623 non-null  int64\n",
      " 8   click_referrer_type  1112623 non-null  int64\n",
      " 9   rank                 1112623 non-null  int32\n",
      " 10  click_cnts           1112623 non-null  int64\n",
      " 11  category_id          1112623 non-null  int64\n",
      " 12  created_at_ts        1112623 non-null  int64\n",
      " 13  words_count          1112623 non-null  int64\n",
      "dtypes: int32(1), int64(13)\n",
      "memory usage: 123.1 MB\n"
     ]
    }
   ],
   "source": [
    "#用户点击日志信息\n",
    "trn_click.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>click_article_id</th>\n",
       "      <th>click_timestamp</th>\n",
       "      <th>click_environment</th>\n",
       "      <th>click_deviceGroup</th>\n",
       "      <th>click_os</th>\n",
       "      <th>click_country</th>\n",
       "      <th>click_region</th>\n",
       "      <th>click_referrer_type</th>\n",
       "      <th>rank</th>\n",
       "      <th>click_cnts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.112623e+06</td>\n",
       "      <td>1.112623e+06</td>\n",
       "      <td>1.112623e+06</td>\n",
       "      <td>1.112623e+06</td>\n",
       "      <td>1.112623e+06</td>\n",
       "      <td>1.112623e+06</td>\n",
       "      <td>1.112623e+06</td>\n",
       "      <td>1.112623e+06</td>\n",
       "      <td>1.112623e+06</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>1.112623e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.221198e+05</td>\n",
       "      <td>1.951541e+05</td>\n",
       "      <td>1.507588e+12</td>\n",
       "      <td>3.947786e+00</td>\n",
       "      <td>1.815981e+00</td>\n",
       "      <td>1.301976e+01</td>\n",
       "      <td>1.310776e+00</td>\n",
       "      <td>1.813587e+01</td>\n",
       "      <td>1.910063e+00</td>\n",
       "      <td>15.521785</td>\n",
       "      <td>1.323704e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5.540349e+04</td>\n",
       "      <td>9.292286e+04</td>\n",
       "      <td>3.363466e+08</td>\n",
       "      <td>3.276715e-01</td>\n",
       "      <td>1.035170e+00</td>\n",
       "      <td>6.967844e+00</td>\n",
       "      <td>1.618264e+00</td>\n",
       "      <td>7.105832e+00</td>\n",
       "      <td>1.220012e+00</td>\n",
       "      <td>33.957702</td>\n",
       "      <td>1.631503e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>1.507030e+12</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7.934700e+04</td>\n",
       "      <td>1.239090e+05</td>\n",
       "      <td>1.507297e+12</td>\n",
       "      <td>4.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.300000e+01</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.309670e+05</td>\n",
       "      <td>2.038900e+05</td>\n",
       "      <td>1.507596e+12</td>\n",
       "      <td>4.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.700000e+01</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.100000e+01</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.704010e+05</td>\n",
       "      <td>2.777120e+05</td>\n",
       "      <td>1.507841e+12</td>\n",
       "      <td>4.000000e+00</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>1.700000e+01</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.500000e+01</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1.600000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.999990e+05</td>\n",
       "      <td>3.640460e+05</td>\n",
       "      <td>1.510603e+12</td>\n",
       "      <td>4.000000e+00</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>2.000000e+01</td>\n",
       "      <td>1.100000e+01</td>\n",
       "      <td>2.800000e+01</td>\n",
       "      <td>7.000000e+00</td>\n",
       "      <td>938.000000</td>\n",
       "      <td>2.410000e+02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            user_id  click_article_id  click_timestamp  click_environment  \\\n",
       "count  1.112623e+06      1.112623e+06     1.112623e+06       1.112623e+06   \n",
       "mean   1.221198e+05      1.951541e+05     1.507588e+12       3.947786e+00   \n",
       "std    5.540349e+04      9.292286e+04     3.363466e+08       3.276715e-01   \n",
       "min    0.000000e+00      3.000000e+00     1.507030e+12       1.000000e+00   \n",
       "25%    7.934700e+04      1.239090e+05     1.507297e+12       4.000000e+00   \n",
       "50%    1.309670e+05      2.038900e+05     1.507596e+12       4.000000e+00   \n",
       "75%    1.704010e+05      2.777120e+05     1.507841e+12       4.000000e+00   \n",
       "max    1.999990e+05      3.640460e+05     1.510603e+12       4.000000e+00   \n",
       "\n",
       "       click_deviceGroup      click_os  click_country  click_region  \\\n",
       "count       1.112623e+06  1.112623e+06   1.112623e+06  1.112623e+06   \n",
       "mean        1.815981e+00  1.301976e+01   1.310776e+00  1.813587e+01   \n",
       "std         1.035170e+00  6.967844e+00   1.618264e+00  7.105832e+00   \n",
       "min         1.000000e+00  2.000000e+00   1.000000e+00  1.000000e+00   \n",
       "25%         1.000000e+00  2.000000e+00   1.000000e+00  1.300000e+01   \n",
       "50%         1.000000e+00  1.700000e+01   1.000000e+00  2.100000e+01   \n",
       "75%         3.000000e+00  1.700000e+01   1.000000e+00  2.500000e+01   \n",
       "max         5.000000e+00  2.000000e+01   1.100000e+01  2.800000e+01   \n",
       "\n",
       "       click_referrer_type           rank    click_cnts  \n",
       "count         1.112623e+06  518010.000000  1.112623e+06  \n",
       "mean          1.910063e+00      15.521785  1.323704e+01  \n",
       "std           1.220012e+00      33.957702  1.631503e+01  \n",
       "min           1.000000e+00       1.000000  2.000000e+00  \n",
       "25%           1.000000e+00       4.000000  4.000000e+00  \n",
       "50%           2.000000e+00       8.000000  8.000000e+00  \n",
       "75%           2.000000e+00      18.000000  1.600000e+01  \n",
       "max           7.000000e+00     938.000000  2.410000e+02  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trn_click.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#训练集中的用户数量为20w\n",
    "trn_click.user_id.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T16:03:01.378461Z",
     "start_time": "2020-11-13T16:03:01.300712Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trn_click.groupby('user_id')['click_article_id'].count().min()  # 训练集里面每个用户至少点击了两篇文章"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 画直方图大体看一下基本的属性分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1440 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.figure(figsize=(15, 20))\n",
    "i = 1\n",
    "for col in ['click_article_id', 'click_timestamp', 'click_environment', 'click_deviceGroup', 'click_os', 'click_country', \n",
    "            'click_region', 'click_referrer_type', 'rank', 'click_cnts']:\n",
    "    plot_envs = plt.subplot(5, 2, i)\n",
    "    i += 1\n",
    "    v = trn_click[col].value_counts().reset_index()[:10]\n",
    "    fig = sns.barplot(x=v['index'], y=v[col])\n",
    "    for item in fig.get_xticklabels():\n",
    "        item.set_rotation(90)\n",
    "    plt.title(col)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从点击时间clik_timestamp来看，分布较为平均，可不做特殊处理。由于时间戳是13位的，后续将时间格式转换成10位方便计算。\n",
    "\n",
    "从点击环境click_environment来看，仅有1922次（占0.1%）点击环境为1；仅有24617次（占2.3%）点击环境为2；剩余（占97.6%）点击环境为4。\n",
    "\n",
    "从点击设备组click_deviceGroup来看，设备1占大部分（60.4%），设备3占36%。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试集用户点击日志"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>click_article_id</th>\n",
       "      <th>click_timestamp</th>\n",
       "      <th>click_environment</th>\n",
       "      <th>click_deviceGroup</th>\n",
       "      <th>click_os</th>\n",
       "      <th>click_country</th>\n",
       "      <th>click_region</th>\n",
       "      <th>click_referrer_type</th>\n",
       "      <th>category_id</th>\n",
       "      <th>created_at_ts</th>\n",
       "      <th>words_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>249999</td>\n",
       "      <td>160974</td>\n",
       "      <td>1506959142820</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "      <td>1506912747000</td>\n",
       "      <td>259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>249999</td>\n",
       "      <td>160417</td>\n",
       "      <td>1506959172820</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "      <td>1506942089000</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>249998</td>\n",
       "      <td>160974</td>\n",
       "      <td>1506959056066</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "      <td>1506912747000</td>\n",
       "      <td>259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>249998</td>\n",
       "      <td>202557</td>\n",
       "      <td>1506959086066</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>327</td>\n",
       "      <td>1506938401000</td>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>249997</td>\n",
       "      <td>183665</td>\n",
       "      <td>1506959088613</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>301</td>\n",
       "      <td>1500895686000</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  click_article_id  click_timestamp  click_environment  \\\n",
       "0   249999            160974    1506959142820                  4   \n",
       "1   249999            160417    1506959172820                  4   \n",
       "2   249998            160974    1506959056066                  4   \n",
       "3   249998            202557    1506959086066                  4   \n",
       "4   249997            183665    1506959088613                  4   \n",
       "\n",
       "   click_deviceGroup  click_os  click_country  click_region  \\\n",
       "0                  1        17              1            13   \n",
       "1                  1        17              1            13   \n",
       "2                  1        12              1            13   \n",
       "3                  1        12              1            13   \n",
       "4                  1        17              1            15   \n",
       "\n",
       "   click_referrer_type  category_id  created_at_ts  words_count  \n",
       "0                    2          281  1506912747000          259  \n",
       "1                    2          281  1506942089000          173  \n",
       "2                    2          281  1506912747000          259  \n",
       "3                    2          327  1506938401000          219  \n",
       "4                    5          301  1500895686000          256  "
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tst_click = tst_click.merge(item_df, how='left', on=['click_article_id'])\n",
    "tst_click.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>click_article_id</th>\n",
       "      <th>click_timestamp</th>\n",
       "      <th>click_environment</th>\n",
       "      <th>click_deviceGroup</th>\n",
       "      <th>click_os</th>\n",
       "      <th>click_country</th>\n",
       "      <th>click_region</th>\n",
       "      <th>click_referrer_type</th>\n",
       "      <th>rank</th>\n",
       "      <th>click_cnts</th>\n",
       "      <th>category_id</th>\n",
       "      <th>created_at_ts</th>\n",
       "      <th>words_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>518010.000000</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>5.180100e+05</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>518010.000000</td>\n",
       "      <td>5.180100e+05</td>\n",
       "      <td>518010.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>227342.428169</td>\n",
       "      <td>193803.792550</td>\n",
       "      <td>1.507387e+12</td>\n",
       "      <td>3.947300</td>\n",
       "      <td>1.738285</td>\n",
       "      <td>13.628467</td>\n",
       "      <td>1.348209</td>\n",
       "      <td>18.250250</td>\n",
       "      <td>1.819614</td>\n",
       "      <td>15.521785</td>\n",
       "      <td>30.043586</td>\n",
       "      <td>305.324961</td>\n",
       "      <td>1.506883e+12</td>\n",
       "      <td>210.966331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14613.907188</td>\n",
       "      <td>88279.388177</td>\n",
       "      <td>3.706127e+08</td>\n",
       "      <td>0.323916</td>\n",
       "      <td>1.020858</td>\n",
       "      <td>6.625564</td>\n",
       "      <td>1.703524</td>\n",
       "      <td>7.060798</td>\n",
       "      <td>1.082657</td>\n",
       "      <td>33.957702</td>\n",
       "      <td>56.868021</td>\n",
       "      <td>110.411513</td>\n",
       "      <td>5.816668e+09</td>\n",
       "      <td>83.040065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>200000.000000</td>\n",
       "      <td>137.000000</td>\n",
       "      <td>1.506959e+12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.265812e+12</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>214926.000000</td>\n",
       "      <td>128551.000000</td>\n",
       "      <td>1.507026e+12</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>1.506970e+12</td>\n",
       "      <td>176.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>229109.000000</td>\n",
       "      <td>199197.000000</td>\n",
       "      <td>1.507308e+12</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>323.000000</td>\n",
       "      <td>1.507249e+12</td>\n",
       "      <td>199.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>240182.000000</td>\n",
       "      <td>272143.000000</td>\n",
       "      <td>1.507666e+12</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>399.000000</td>\n",
       "      <td>1.507630e+12</td>\n",
       "      <td>232.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>249999.000000</td>\n",
       "      <td>364043.000000</td>\n",
       "      <td>1.508832e+12</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>938.000000</td>\n",
       "      <td>938.000000</td>\n",
       "      <td>460.000000</td>\n",
       "      <td>1.509949e+12</td>\n",
       "      <td>3082.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             user_id  click_article_id  click_timestamp  click_environment  \\\n",
       "count  518010.000000     518010.000000     5.180100e+05      518010.000000   \n",
       "mean   227342.428169     193803.792550     1.507387e+12           3.947300   \n",
       "std     14613.907188      88279.388177     3.706127e+08           0.323916   \n",
       "min    200000.000000        137.000000     1.506959e+12           1.000000   \n",
       "25%    214926.000000     128551.000000     1.507026e+12           4.000000   \n",
       "50%    229109.000000     199197.000000     1.507308e+12           4.000000   \n",
       "75%    240182.000000     272143.000000     1.507666e+12           4.000000   \n",
       "max    249999.000000     364043.000000     1.508832e+12           4.000000   \n",
       "\n",
       "       click_deviceGroup       click_os  click_country   click_region  \\\n",
       "count      518010.000000  518010.000000  518010.000000  518010.000000   \n",
       "mean            1.738285      13.628467       1.348209      18.250250   \n",
       "std             1.020858       6.625564       1.703524       7.060798   \n",
       "min             1.000000       2.000000       1.000000       1.000000   \n",
       "25%             1.000000      12.000000       1.000000      13.000000   \n",
       "50%             1.000000      17.000000       1.000000      21.000000   \n",
       "75%             3.000000      17.000000       1.000000      25.000000   \n",
       "max             5.000000      20.000000      11.000000      28.000000   \n",
       "\n",
       "       click_referrer_type           rank     click_cnts    category_id  \\\n",
       "count        518010.000000  518010.000000  518010.000000  518010.000000   \n",
       "mean              1.819614      15.521785      30.043586     305.324961   \n",
       "std               1.082657      33.957702      56.868021     110.411513   \n",
       "min               1.000000       1.000000       1.000000       1.000000   \n",
       "25%               1.000000       4.000000      10.000000     252.000000   \n",
       "50%               2.000000       8.000000      19.000000     323.000000   \n",
       "75%               2.000000      18.000000      35.000000     399.000000   \n",
       "max               7.000000     938.000000     938.000000     460.000000   \n",
       "\n",
       "       created_at_ts    words_count  \n",
       "count   5.180100e+05  518010.000000  \n",
       "mean    1.506883e+12     210.966331  \n",
       "std     5.816668e+09      83.040065  \n",
       "min     1.265812e+12       0.000000  \n",
       "25%     1.506970e+12     176.000000  \n",
       "50%     1.507249e+12     199.000000  \n",
       "75%     1.507630e+12     232.000000  \n",
       "max     1.509949e+12    3082.000000  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tst_click.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以看出训练集和测试集的用户是完全不一样的\n",
    "\n",
    "训练集的用户ID由0 ~ 199999，而测试集A的用户ID由200000 ~ 249999。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#测试集中的用户数量为5w\n",
    "tst_click.user_id.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:56:07.717463Z",
     "start_time": "2020-11-13T15:56:07.693494Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tst_click.groupby('user_id')['click_article_id'].count().min() # 注意测试集里面有只点击过一次文章的用户"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 新闻文章信息数据表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:20:34.183761Z",
     "start_time": "2020-11-13T15:20:34.164770Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>click_article_id</th>\n",
       "      <th>category_id</th>\n",
       "      <th>created_at_ts</th>\n",
       "      <th>words_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1513144419000</td>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1405341936000</td>\n",
       "      <td>189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1408667706000</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1408468313000</td>\n",
       "      <td>230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1407071171000</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364042</th>\n",
       "      <td>364042</td>\n",
       "      <td>460</td>\n",
       "      <td>1434034118000</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364043</th>\n",
       "      <td>364043</td>\n",
       "      <td>460</td>\n",
       "      <td>1434148472000</td>\n",
       "      <td>463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364044</th>\n",
       "      <td>364044</td>\n",
       "      <td>460</td>\n",
       "      <td>1457974279000</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364045</th>\n",
       "      <td>364045</td>\n",
       "      <td>460</td>\n",
       "      <td>1515964737000</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364046</th>\n",
       "      <td>364046</td>\n",
       "      <td>460</td>\n",
       "      <td>1505811330000</td>\n",
       "      <td>479</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        click_article_id  category_id  created_at_ts  words_count\n",
       "0                      0            0  1513144419000          168\n",
       "1                      1            1  1405341936000          189\n",
       "2                      2            1  1408667706000          250\n",
       "3                      3            1  1408468313000          230\n",
       "4                      4            1  1407071171000          162\n",
       "364042            364042          460  1434034118000          144\n",
       "364043            364043          460  1434148472000          463\n",
       "364044            364044          460  1457974279000          177\n",
       "364045            364045          460  1515964737000          126\n",
       "364046            364046          460  1505811330000          479"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#新闻文章数据集浏览\n",
    "item_df.head().append(item_df.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:28:13.084501Z",
     "start_time": "2020-11-13T15:28:13.062561Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "176     3485\n",
       "182     3480\n",
       "179     3463\n",
       "178     3458\n",
       "174     3456\n",
       "        ... \n",
       "845        1\n",
       "710        1\n",
       "965        1\n",
       "847        1\n",
       "1535       1\n",
       "Name: words_count, Length: 866, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_df['words_count'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:28:59.029535Z",
     "start_time": "2020-11-13T15:28:58.816106Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "461\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20d37480320>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(item_df['category_id'].nunique())     # 461个文章主题\n",
    "item_df['category_id'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(364047, 4)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_df.shape       # 364047篇文章"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 新闻文章embedding向量表示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>article_id</th>\n",
       "      <th>emb_0</th>\n",
       "      <th>emb_1</th>\n",
       "      <th>emb_2</th>\n",
       "      <th>emb_3</th>\n",
       "      <th>emb_4</th>\n",
       "      <th>emb_5</th>\n",
       "      <th>emb_6</th>\n",
       "      <th>emb_7</th>\n",
       "      <th>emb_8</th>\n",
       "      <th>...</th>\n",
       "      <th>emb_240</th>\n",
       "      <th>emb_241</th>\n",
       "      <th>emb_242</th>\n",
       "      <th>emb_243</th>\n",
       "      <th>emb_244</th>\n",
       "      <th>emb_245</th>\n",
       "      <th>emb_246</th>\n",
       "      <th>emb_247</th>\n",
       "      <th>emb_248</th>\n",
       "      <th>emb_249</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>-0.161183</td>\n",
       "      <td>-0.957233</td>\n",
       "      <td>-0.137944</td>\n",
       "      <td>0.050855</td>\n",
       "      <td>0.830055</td>\n",
       "      <td>0.901365</td>\n",
       "      <td>-0.335148</td>\n",
       "      <td>-0.559561</td>\n",
       "      <td>-0.500603</td>\n",
       "      <td>...</td>\n",
       "      <td>0.321248</td>\n",
       "      <td>0.313999</td>\n",
       "      <td>0.636412</td>\n",
       "      <td>0.169179</td>\n",
       "      <td>0.540524</td>\n",
       "      <td>-0.813182</td>\n",
       "      <td>0.286870</td>\n",
       "      <td>-0.231686</td>\n",
       "      <td>0.597416</td>\n",
       "      <td>0.409623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>-0.523216</td>\n",
       "      <td>-0.974058</td>\n",
       "      <td>0.738608</td>\n",
       "      <td>0.155234</td>\n",
       "      <td>0.626294</td>\n",
       "      <td>0.485297</td>\n",
       "      <td>-0.715657</td>\n",
       "      <td>-0.897996</td>\n",
       "      <td>-0.359747</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.487843</td>\n",
       "      <td>0.823124</td>\n",
       "      <td>0.412688</td>\n",
       "      <td>-0.338654</td>\n",
       "      <td>0.320786</td>\n",
       "      <td>0.588643</td>\n",
       "      <td>-0.594137</td>\n",
       "      <td>0.182828</td>\n",
       "      <td>0.397090</td>\n",
       "      <td>-0.834364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>-0.619619</td>\n",
       "      <td>-0.972960</td>\n",
       "      <td>-0.207360</td>\n",
       "      <td>-0.128861</td>\n",
       "      <td>0.044748</td>\n",
       "      <td>-0.387535</td>\n",
       "      <td>-0.730477</td>\n",
       "      <td>-0.066126</td>\n",
       "      <td>-0.754899</td>\n",
       "      <td>...</td>\n",
       "      <td>0.454756</td>\n",
       "      <td>0.473184</td>\n",
       "      <td>0.377866</td>\n",
       "      <td>-0.863887</td>\n",
       "      <td>-0.383365</td>\n",
       "      <td>0.137721</td>\n",
       "      <td>-0.810877</td>\n",
       "      <td>-0.447580</td>\n",
       "      <td>0.805932</td>\n",
       "      <td>-0.285284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>-0.740843</td>\n",
       "      <td>-0.975749</td>\n",
       "      <td>0.391698</td>\n",
       "      <td>0.641738</td>\n",
       "      <td>-0.268645</td>\n",
       "      <td>0.191745</td>\n",
       "      <td>-0.825593</td>\n",
       "      <td>-0.710591</td>\n",
       "      <td>-0.040099</td>\n",
       "      <td>...</td>\n",
       "      <td>0.271535</td>\n",
       "      <td>0.036040</td>\n",
       "      <td>0.480029</td>\n",
       "      <td>-0.763173</td>\n",
       "      <td>0.022627</td>\n",
       "      <td>0.565165</td>\n",
       "      <td>-0.910286</td>\n",
       "      <td>-0.537838</td>\n",
       "      <td>0.243541</td>\n",
       "      <td>-0.885329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>-0.279052</td>\n",
       "      <td>-0.972315</td>\n",
       "      <td>0.685374</td>\n",
       "      <td>0.113056</td>\n",
       "      <td>0.238315</td>\n",
       "      <td>0.271913</td>\n",
       "      <td>-0.568816</td>\n",
       "      <td>0.341194</td>\n",
       "      <td>-0.600554</td>\n",
       "      <td>...</td>\n",
       "      <td>0.238286</td>\n",
       "      <td>0.809268</td>\n",
       "      <td>0.427521</td>\n",
       "      <td>-0.615932</td>\n",
       "      <td>-0.503697</td>\n",
       "      <td>0.614450</td>\n",
       "      <td>-0.917760</td>\n",
       "      <td>-0.424061</td>\n",
       "      <td>0.185484</td>\n",
       "      <td>-0.580292</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 251 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   article_id     emb_0     emb_1     emb_2     emb_3     emb_4     emb_5  \\\n",
       "0           0 -0.161183 -0.957233 -0.137944  0.050855  0.830055  0.901365   \n",
       "1           1 -0.523216 -0.974058  0.738608  0.155234  0.626294  0.485297   \n",
       "2           2 -0.619619 -0.972960 -0.207360 -0.128861  0.044748 -0.387535   \n",
       "3           3 -0.740843 -0.975749  0.391698  0.641738 -0.268645  0.191745   \n",
       "4           4 -0.279052 -0.972315  0.685374  0.113056  0.238315  0.271913   \n",
       "\n",
       "      emb_6     emb_7     emb_8  ...   emb_240   emb_241   emb_242   emb_243  \\\n",
       "0 -0.335148 -0.559561 -0.500603  ...  0.321248  0.313999  0.636412  0.169179   \n",
       "1 -0.715657 -0.897996 -0.359747  ... -0.487843  0.823124  0.412688 -0.338654   \n",
       "2 -0.730477 -0.066126 -0.754899  ...  0.454756  0.473184  0.377866 -0.863887   \n",
       "3 -0.825593 -0.710591 -0.040099  ...  0.271535  0.036040  0.480029 -0.763173   \n",
       "4 -0.568816  0.341194 -0.600554  ...  0.238286  0.809268  0.427521 -0.615932   \n",
       "\n",
       "    emb_244   emb_245   emb_246   emb_247   emb_248   emb_249  \n",
       "0  0.540524 -0.813182  0.286870 -0.231686  0.597416  0.409623  \n",
       "1  0.320786  0.588643 -0.594137  0.182828  0.397090 -0.834364  \n",
       "2 -0.383365  0.137721 -0.810877 -0.447580  0.805932 -0.285284  \n",
       "3  0.022627  0.565165 -0.910286 -0.537838  0.243541 -0.885329  \n",
       "4 -0.503697  0.614450 -0.917760 -0.424061  0.185484 -0.580292  \n",
       "\n",
       "[5 rows x 251 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_emb_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(364047, 251)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_emb_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 用户重复点击"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:30:20.899771Z",
     "start_time": "2020-11-13T15:30:20.750817Z"
    }
   },
   "outputs": [],
   "source": [
    "#####merge\n",
    "user_click_merge = trn_click.append(tst_click)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:30:26.290038Z",
     "start_time": "2020-11-13T15:30:25.339579Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>click_article_id</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>30760</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>157507</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>63746</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>289197</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>36162</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2</td>\n",
       "      <td>168401</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3</td>\n",
       "      <td>36162</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3</td>\n",
       "      <td>50644</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4</td>\n",
       "      <td>39894</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>4</td>\n",
       "      <td>42567</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  click_article_id  count\n",
       "0        0             30760      1\n",
       "1        0            157507      1\n",
       "2        1             63746      1\n",
       "3        1            289197      1\n",
       "4        2             36162      1\n",
       "5        2            168401      1\n",
       "6        3             36162      1\n",
       "7        3             50644      1\n",
       "8        4             39894      1\n",
       "9        4             42567      1"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#用户重复点击\n",
    "user_click_count = user_click_merge.groupby(['user_id', 'click_article_id'])['click_timestamp'].agg({'count'}).reset_index()\n",
    "user_click_count[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:34:27.418638Z",
     "start_time": "2020-11-13T15:34:27.372761Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>click_article_id</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>311242</th>\n",
       "      <td>86295</td>\n",
       "      <td>74254</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311243</th>\n",
       "      <td>86295</td>\n",
       "      <td>76268</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393761</th>\n",
       "      <td>103237</td>\n",
       "      <td>205948</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393763</th>\n",
       "      <td>103237</td>\n",
       "      <td>235689</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576902</th>\n",
       "      <td>134850</td>\n",
       "      <td>69463</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        user_id  click_article_id  count\n",
       "311242    86295             74254     10\n",
       "311243    86295             76268     10\n",
       "393761   103237            205948     10\n",
       "393763   103237            235689     10\n",
       "576902   134850             69463     13"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_click_count[user_click_count['count']>7]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:32:53.298575Z",
     "start_time": "2020-11-13T15:32:53.285611Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  2,  4,  3,  6,  5, 10,  7, 13], dtype=int64)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_click_count['count'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1     1605541\n",
       "2       11621\n",
       "3         422\n",
       "4          77\n",
       "5          26\n",
       "6          12\n",
       "10          4\n",
       "7           3\n",
       "13          1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#用户点击新闻次数\n",
    "user_click_count.loc[:,'count'].value_counts() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### 可以看出：有1605541（约占99.2%）的用户未重复阅读过文章，仅有极少数用户重复点击过某篇文章。 这个也可以单独制作成特征"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 用户点击环境变化分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:39:41.961797Z",
     "start_time": "2020-11-13T15:39:41.949829Z"
    }
   },
   "outputs": [],
   "source": [
    "def plot_envs(df, cols, r, c):\n",
    "    plt.figure()\n",
    "    plt.figure(figsize=(10, 5))\n",
    "    i = 1\n",
    "    for col in cols:\n",
    "        plt.subplot(r, c, i)\n",
    "        i += 1\n",
    "        v = df[col].value_counts().reset_index()\n",
    "        fig = sns.barplot(x=v['index'], y=v[col])\n",
    "        for item in fig.get_xticklabels():\n",
    "            item.set_rotation(90)\n",
    "        plt.title(col)\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:39:55.476626Z",
     "start_time": "2020-11-13T15:39:48.764592Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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4IUr0GNGPG4EtACSNIt2lmt/XjhFxTkRMjIiJq6yyyhBPazaijQMui4gorPtc/vkw6QGaZjhfzbqDc9WsCWUfljse+LmkqaSq1sUAEfGXEsc4Bzhb0gJgO9Kdqt+XjMPMlnQVcLWk/wTuIVWLzpX0UVJTiSubPK7z1azNJI2OiFckvREYFxG3NHEY56pZE8oWhI/LP88urOu3jXBfIuJqSUeQCtULgH+OiEG7YjOzAX0WOAI4lSUfonmC1I3SV5o5qPPVrL0kHQhsK2kKqU3/cpIuiIgDyxzHuWrWnLK9RpSuXo2IeaRq2+K6C0htGs2sBSLiJeBI4EhJy5N6dnkxIko1AHS+mg27rwIbAdsD/0OqwZkLDFgQdq6atUapNsKSRkk6RNJNkmZJ+mpui2RmHSL3I7olcJCk5SR9PY86ZWadR6QH3TYjFYSfpfzzO2bWpLLJdgLpW+sJwImkdkjHtzooM2uepDOALwL7AS+TRpo7a8BfMrOq/Aa4E9gNuI40AuSvK43IrIeUbSO8C/CuiHgWQNI1pAQ+tNWBmVnTdiL1J3xvRLwg6RPAvGpDMrN+fIZ0g+lPEfGEpKuBn1Yck1nPKHtH+EVgTGF55bzOzDrHM8DrSQ+yArwFeKG6cMysPxHxInAFsIyktYHzI6LZfr/NrKRmeo2YJekS0kV2CnB4y6Mys6E4CbgWWF7SKaQ7xCdUG5KZ9UXSO4DLSUMkA8yXtGNE/LnCsMx6RtleI86TdDewQ161a0Tc2PqwzKxZEfE9SXNJ1a0A+0TEtVXGZGb9Ohs4OyJOB5D0BVKfwJMrjcqsR5S9I0wu+Lrwa9bBcsH3WknLuJrVrKOtGxEfrC1ExJm5P2AzGwZlu0/7uqRl2hWMmQ2dpImSbs+Ln5E0X9JGlQZlZv25S1JtOHQk7QvcVWE8Zj2l7MNyu7HkqFVm1nm+R2onDKnbtINw92lmnWo/4ABJj0t6jDSQxn4Vx2TWM8oWhL8BnJRHrjKzzjQ2Is4DiIjFEXEprz6IY2YdJCLuAdYnDaixObB+XoekCVXGZtYLyrYRPghYG7hf0q21lRGxTUujMrOhuF3SPrXCsKS9gLsrjsnM+hERrwB39LFpJrDaMIdj1lPKFoSntiMIM2upzwNXSDo5Lz8CfKLCeMysOao6ALORrmz3ade1KxAza42ImCtpXVLtjYC78h0nM+suMfguZjYUpbtPM7PON0BVq5mZmWVlH5YzMzMzMxsRBr0jLOngiDglzx/Z1z4RcUyrAzOzxknaOSIuyfN79rVPRJw/vFGZ2RC5jbBZmzXSNEL9zJtZ59gMuCTPb93H9gBcEDbrApKWioiXgZ2qjsVspBu0IBwRJxfmj25vOGbWjIg4sDC/T5WxmFnjJE2JiOmF5W2BU4F3R8Ss6iIz6w1+WM7MzKw6R0laCriJVACeQBpdzsyGQamCsKQ3RsST7QrGzIZOkiLC3S6ZdYfJwC+A1Umjt54bEYurDcmsd5TtNWKepOmSdpS0dFsiMrOhelDSSZI2qjoQMxtYRDxCKgzfB8iFYLPhVbYgvBrpgZuPAbdJOkfSFq0Py8yG4P3AX4CTJN0s6euSxlUbkpnVSFos6ZXaBCwEJgFn17ZVHKJZzyhVEI6I5yPiZxHxGWBDYAHw67ZEZmZNiYj5EfGfETEZ2ApYDphbbVRmVhMRoyJidN00qjCNrjpGs15RqiAsaUVJe0i6GLgZWJbUbZOZdQglm0k6EbgOWBf414rDMrN+SNok/9xA0uSq4zHrJWV7jbgf+BnwX8Cv3JbJrCM9DNwFXAhsGRGPVxyPmfVD0iHAwcCqwFuBsySdHhHfqTYys95QtiC8WkQ815ZIzKxVNo2I+VUHYWYNOQDYACAirpG0KTAbcEHYbBiULQi/QdK+wIrFlR5i2axzRMR8Se8nXVzPA3aKiAsrDsvM+hbAosLyM7iPf7NhU7bXiCuBj+TfU2Eysw4h6QjgAuA4Un5+RdLx1UZlZv2YDlwhaQdJHwcuzZOZDYOy3zrXiohV2hKJmbXK/sB6wG0R8ZykzUlthg+rNiwz68MhwNdIg2kI+DnwrUojMushZQvCMyRtGxFXtyUaM2uFF4DnSFWuAEsX5s2sg0TES8CxeTKzYVa2IDwPmC7pSlK/pIvBbYTNOsw04DJSm/4DgE/ldWZmZlZQto3w08BJpGrWYAhthCVdI2mBpIfztE8zxzGzJUXE0cBFpMFuPgCcGRFHNXs856pZ93C+mpVT6o5wvsC2yobAGhHxbAuPaWZARJxH6jGiFZyrZi0kaXpETMnz19JH06WI2KbJwztfzUooVRCW9E7gDGBtYCNgFrBzRNxc8jgTgIedqGatIel+BmkHHBETmjiuc9Ws9U4uzE9t1UGdr2bllW0jfB5wCbBeRCyUNBU4B5hU8jibAqtKehB4A/BT4ICIeLnkccws2aowfwCwEnAaqR3//kM4rnPVrMUiYlZh/roWHtr5alZS2TbCawLfJd95yp30v72J874MnACMB9YCNgH2rt9J0n6SZkuavWDBgiZOY9YbImJ+bQJ2jIhPR8QfI+LmiPg8sH2Th24oV8H5atYBfG01K6lsQXgu8CFyQVjSp4A/lz1pREyPiJMj4qWIeIz0RPt2fex3TkRMjIiJq6zi7ovNGvScpE/UFiRtDzRVVdporuZ9na9mFfK11ay8sk0j9id1y/QWSY8BC4Edy55U0q7A/0bEI3nV6sArZY9jZn3aH7hI0g9IX1oXA7s1cyDnqln3cL6alVe214jbJa1DelgOYG6t7ZGkCRFxX4OHmgRsI+ngfKx9gC+WicXM+hYR10saR8qtUaQ8fR5K5yk4V81aTtKeg+0TEec3cWjnq1lJZe8Ikwu+t/exaSawWoOHOQq4APg78CBwbET8d9lYzKxvEfEicGsfm8rkKThXzdph60G2B9BMQdj5alZS6YLwABoeWCMingR2aOG5zawxpQbAca6atV5EtGWQC+erWXllH5YbyIB9mJpZR3CempmZZa0sCJuZmVkJksZIOiPP7ybpAkkrVx2XWa9wQdjMzKw65wKvy/MzgUeB71cXjllvqaSNsJlVxnlq1lkmAW8DiIgHco8PD1YbklnvGPIdYUm1wvROQz2WmbWH89SsYz0KrFNYXgd4oqJYzHpOqYKwpCl1y9uSu2gqjp1uZtVxnpp1lUOB6yRdJulS4Lq8zsyGQdmmEUflO0s3AacCE4ADWx6VmQ2F89SsS0TElZImAR8mNV06JCLurTgss55RtiA8GfgFadjGbwDnRsTilkdlZkPhPDXrIrng68KvWQVKNY3I45dPBu4D5IurWedxnpqZmTVm0DvCkhbz2k74BUySdDYQETG6HcGZWWOcp2ZmZuUNWhCOCPc1bNbhnKdmZmbllb54Stok/9xA0uTWh2RmQ+U8NTMzG1zZ7tMOAX6eF98KnCPpoJZHZWZNc56amZk1puwd4QOADQAi4hpg07zOzDqH89TMzKwBZQvCASwqLD9Da4dpNrOhc56amZk1oOzFcTpwhaSzSBfbzwOXtjwqMxsK56mZmVkDyhaEDwG+RuqkX6R2iN9qdVBmNiTOUzMzswaUKghHxEvAsXkysw7kPDUzM2uM+x41MzMzs57kgrCZmZmZ9aRGhlieHhFT8vy1vHYYVyJimzbEZmYNcp6amZmV10gb4ZML81PbFIeZDY3z1MzMrKRBC8IRMaswf117wzGzZjhPzczMynMbYTMzMzPrSS4Im5mZmVlPckHYzMzMzHpSI71G7DnYPhFxfmvCMbNmOE/NzMzKa6TXiK0H2R6AL7Bm1XKempmZldRIrxH7DEcgZtY856mZmVl5biNsZmZmZj2pVEFY0hhJZ+T53SRdIGnl9oRmZs1wnpqZmTWm7B3hc4HX5fmZwKPA95s5saStJN0p6SFJRzRzDDPrU8vytMb5atYdnKtm5ZQtCE8CPgcQEQ8AB+d1pUhaCbgM+AYwFtha0nZlj2NmfWpJntY4X826g3PVrLyyBeFHgXUKy+sATzRx3u2B+yLi0oh4CTgN2L2J45jZa7UqT2ucr2bdwblqVlIj3acVHQpcJ+l6UndMWwDNPK0+FphTWL4PWLuJ45jZa7UqT2ucr2bdwblqVlKpgnBEXClpEvBhQMAhEXFvE+cdBSwqLD8DrFi/k6T9gP3y4tOS5jZxLmveGNLdRRuETtqrVYdaY6gHaGGe1jhfu4PztQEtzFVoQb62mHO1OzhXGzQc19ayd4TJF9ShXFQBFrJkUMsCr/RxrnOAc4Z4LmuSpNkRMbHqOKy8FuVpjfO1CzhfDedqV3Cudpaq+hG+kVRdWzMJmF9RLGY2MOerWXdwrpqVVElBOCJuBR6TdKKkycDhwI+riMXMBuZ8NesOzlWz8qocWW4n4G3AycCZEfGjCmOxvrnqzGqcr53P+WrgXO0GztUOooioOgYzMzMzs2FX5R1hMzMzM7PKuCBsZmZmZj3JBWHrl6R/rjoGMzMzs3ZxG2FD0th+Nv0emEh6n/xlGEMys35IWho4mDR09k+A64ATgfVI3WdNzcPrmlmFJC0LHACMA24AfhIRiwvbp0fElIrCs8wFYUPS30kj3dQXdt8OPABEREwY9sDM7DUkHUXqK/Yy4DPAU8CDwE+BTwJPRcTnq4vQzAAkXUy6jv4K+CjweuBfI+JPefvfImK1CkM0XBA2QNIqpO5cVgD2ioi/5vUPRcTbKg3OzJYg6Vpg34i4V9I7gZnAahHxsqTRwPyIWL3aKM1M0vPA2yLi8bz8aeAE4GsR8V++xnYGtxE2ImJBROwI/Ai4QdIna5sqDMvM+vYgsClARNwN7BoRL+dt4wE3izDrDE8A/2h6GBHnApsDX5F0Gi6DdQTfEbYl5PbC5wF/Az4cEW+tOCQzK5C0BvAL4PSIOLOwfjPgZ8BBEXF+VfGZWSLpc8AhwM4R8YfC+pWAq4BJETG6qvgscUHY+iTpQFLyblZ1LGa2JElLAatGxIOFdW8HVoiIO6qLzMyKJG0CvBARt9StXwr4SET8vJrIrMYFYTMzMzPrSW6fYmZmZmY9yQVhMzMzM+tJLgj3CEm7SPpuE7+3laQZbQjJzPrgXDXrDs7VkWGpqgOw4RERPyV1uG9mHcy5atYdnKsjg+8Im5mZmVlPckG4R0jaW9K0wvIMSZ+X9HtJCyX9sLDtXyTdL+keYOfC+mUknS7pwTztm9e/UdJfJG2Zl38u6fDhe3VmI4dz1aw7OFdHBjeN6G3/DmwHPAbMlbQh8DAwDZgM/Am4srD/YcBywJrAqsAcSb+KiHmS9gNOk3QYaWz1nYbtVZiNfM5Vs+7gXO0yviPc206JiD/ncdDvBFYkDd16b0T8LiJeBL5X2P+jwA7APOAm0hep/wcQEb8E/gBcBHwmIjzMq1nrOFfNuoNztcv4jnBvm1uYr42sMgpYXFj/St3vfDoiLodUdQO8WNi2ct5/xRbHadbrnKtm3cG52mV8R7i3Le5j3e+BtSVtKGlpYN/Ctv8B9s1tmsaQvu1OBMjtmt4EfAT4gaQ3tTd0s57iXDXrDs7VLuOCsC0hIv4K7AdcAdwLLChs/iYwP6+fA5wcETMljQeOAz4bEbOAnwOl+1Y0s8Y5V826g3O1sykiBt/LzMzMzGyE8R1hMzMzM+tJLgibmZmZWU9yQdjMzMzMepILwmZmZmbWk1wQNjMzM7Oe5IKwmZmZmfUkF4TNzMzMrCe5IGxmZmZmPckFYTMzMzPrSS4Im5mZmVlPckHYzMzMzHqSC8JmZmZm1pNcEDYzMzOznuSCsJmZmZn1JBeEzczMzKwnuSBcIUkhaat+tm0lKVp5TDNrnV7NX0nzJO1ddRzWvUZq7kj6mKQ7Jb0o6UFJ/6/KeKwxLgh3rpnASlUHMdwkTZM0reo4zIZoJOfv+sCFVQdhI1Y35855pNxYHfgo8HC14bSGpKmSZlQdR7ssVXUA1reIeBlYVHUcZlbeSM7fiHiy6hhs5Ory3BkD3BARjwCPVB2MNcZ3hNtE0jhJl0talKtIjpXU8N+7v+ohSUtJOjJXTz4h6SpJE/o5xub5/FNKnHeKpFskPSNpjqTJhW2jJR0m6T5JCyVdJGnVwvYlqqaKryH/PULSFuu6bnwAACAASURBVJJ+LelZSXdI2iRvvzLvuxewV943JI0rHG9anjaR9BtJ8wrbpku6uO61/E7SNxt97WY1XZy/M/Ldm20lzZJ0fd32XXN+P5VzaEJhmySdLOmxnOPHSfqzpCPqjtFn0whJm0n6bT72HEnbFrbVcvcASX/Lr/3MRl+XdY9eyx1JK9auV3nXa/PyjMLvriDp9Pz3+LukEyUtVdg+NZ9/TUlX5NiXK2zv99qXt38wX++eyj83rtsekraW9GVJcyUd3+Df5PT8uo4Ctixcl7fK2/8t5/Powu+cKOm3hbivkvRLSU9K+oOkzQv7Kn8mzM3/00slrdJIbC0VEZ5aPAHLAvcCPwHGA+8jfTs8sG6/ALbq5xhbpX/Pa9YfD8wHtgTGApcAf6o/JvBeYCEwpUTc2wIvAnsCqwFfA54BVsvbjwb+BkwG1gSuBP4ELN3X6ym+BmBc3n4f8Kn8d7kRuDZvXw5YkVStdGGeXxEYVTjeNOD/gD8D+wKbFbZtDzwHvCkvvwNYDKxV9fvBU3dN3Zq/+fdnANcBdwB7AO8pbPtozom9SVW3Pwbm1nIs5/0DwLuAzwIvAWsDK9edYx6wd926dwHPA4fn1/WF/PvvzdunAQ8Bv8jH3CO/1i2r/n97at3Ui7kDiFevVwF8LM8vX/j96cBdwAbAROCvwDcK26fm894DHARsDYwubJ9G/9e+DXOufT3HdiLwKPDGur/NtcAvc3zvaPBv8ob8Wr5FarJSe51L5e0r5bzfNi8r/4/2LcQdwL8BawCnAo8Dq+Tt/wY8m2MaD/wG+NWwv2+rTpyROAE75zfHsoV1mwPvq9uv1IdBfpM9DXy6sO6fgF149WIWwL+TqpamlYz7KuD8wvLSwK7AqvncTwL7Fba/GXgF+Ghfr4e+C8KHFbZ/Dri/LoZp/cWdt70ErNfHttGkD5fP5uUjSVVUlb8fPHXX1K35m39/Rr7QrNrHtl8AVxaWJ+TzbZKXTwd+kueXydve18dx5vHagvDpwKy6dZcBl+T5acAClrw4PwTsVfX/21Prpl7NnYFeF/DWvH5KYd0xwO2F5al5n+36iW0a/V/7zgJuKywvQ7qhtXNdXDPJBdgm/jZTgRn9bPsp8KM8vwXp5tkKhbhnFfZ9fd7+qbx8J3B6Yfs2OdZVhvN966YR7TEOeDginq2tiIiZETFriMcdQ7pzel/huH+NiJ9GxOLCfseTvnntLGmtEscfV3fslyLiooh4OJ97BeDuwvbHSN88x/dzvOX7WPeLwvwLpA+4Mn4WEbfWr4yIV4ALSHebAXYDzi15bDPo3vytOTfnbL2xwAdztesi4A95fa16+WZgY0nLky5oz5PuejVifB/73s2Snw03xpLti5vJf+ts4+jN3BnI2NqxC7//lT5+9w8R8csBjtPntS8f/52FYz9Mev6r/vgnRGp/3WrnATvmz43dgekR8VRh+7zaTES8QKoheFsh9k8XYr88r2/k79oyLgi3xzxg1bo2PgdKumiIx32U9K34HYXjjpd0m6R3FPb7ckRMBc4Hzihx/HnFY+fjz5C0az73U6Rqzdq2N5M+oO4r/Mrowvz7+jjHYA9BLGbgi+NTA2w7D/iApB1JVUQXD7CvWX/m0Z35W9NfjswHfkiqSq1NGwC/yttvJ9XyPEa6m/u5/GW3EfdR+GzI1mbJz4ZufQDKGjeP3sydgczPP/+l8Lvrk5pwNHLuRmL7VV1s6+d4yxx/IANdl68h3UnfBZjCa29ArVmbkfQG0h3yvxZiP74u7o1In0XDxgXh9rgKeBD4fk7W95GqbG4bykEj1R2cBhyp9NDZGsB/kL79zS/semf+eQSwiaRPNniK7wK7SPqUpNUkHQhsSvqmGsB3gKMkbSNpTVKi3cqrHwbzSFUb5Ne8XxMv807gfZLWkLSWpPoPi35FxFxgFvAD4OKIeKaJ85t1a/4O5gzgE8BapGrWLUl3tmp3zr5Nupu2AelOzQUlj72RpMMlvV3SF0jtKk9pUezWHXo1dwaK/RFSG+EvkpotLAMcS2pH3Qpnk5qfTCQ1iVgfuIlUq9MqdwIbSFpb6WHILWsb8h3580ltkxcB19f97sT8QNxY4ARSTVPtzvcZpPbYq5EK27uQ2kIPb/d5w9kOo5cmUpXgFaQ3xl9ID5qNrtunmQcGliK1f50PPAH8HJjQ3zFJDe8fJLfZaSDuKaTC7TPA74FtCttGA4cB95PuGv2UQnsq0gNr80hVor8k9QCRP8P+0UZ4XGH/vYF5ded/A+lhuSdJdwCKDxRMY5C2X6SHfILCwwSePJWdujh/ZwBTB9i+W87vZ0mFk10K2/YkPXD6BOmi9BzpoaCl644xj7o2wnn9ZqQvok+RCgnbFra9Jnf7O46n7p56MXcGe12kZoVnkO6EPpljH1/YPpV+2uDm7QNe+4APka7Xz5AeVvxSo3/vBv82It0oe4xUkP1e3fa18jm+0Ufcl+fX+wQwB3h/3XG/TCozPAv8Dpg83O9Z5WDMulqucnkL8HHgCxHx7opDMusauX3fQ6QvrzNJF7X3kAo0G0fEsFZVmll3yLXDKwE3kHqj+Gth2zSAiNi7kuAa5AE1ekSulrhlgF1Oi4gjBtje6d5M6p5mIenOltmI0e78jYinJX2XVL35T3n1PFL/oXc0e1yzqvXAta9pkq4kNavoy8KIeEc/24ouJdUCHF4sBHcT3xHuEUqdd68+wC5PRMTjwxWPmTXO+TsySXonqcp8bdJDQrNI3V7dXGlgI4hzp39KA2It08/mVyLigeGMpyouCJuZmVVA0o2kgSG+FhGrStqd1PPBpIpDM+sZLgibmZlVQNLfSQMW/S0i3pbX/S0iVqs2MrPe4e7TzMzMqjGX9MR/eoRe+hRpGF0zGyZdc0d4zJgxMW7cuKrDMGurOXPmPBoRq1Qdx1A5X60XDDVfJa1LGrxkAqlbrYXAjhExpH53y3CuWi8YKFe7pteIcePGMXv27KrDMGsrSfMH36vzOV+tFww1XyPidknr8OqofHOjPcPg9su5ar1goFztmoKwmZnZCLQeqQurV0gDDAzb3WAzcxthMzOzSkj6EmmI+s2BrYEZkvavNiqz3uI7wmZmZtU4lDRy318AJI0jjex3VoUxmfWUniwIv+er51cdgo0wc77tweys8/3lmPWqDqErjD3y1uE61dPAo4XlhaSH5qzHOVcbN9R87cmCsJmZWQeYDVwv6Yekpop7AbMk7QkQEb5rY9ZmLgibmZlV4yXgVmDjvHwzqUC8NalvYReEzdrMBWEzM7NqfDYiXqk6CLNe5l4jzMzMqvGwpNMlTao6ELNe5YKwmf2DpPUk3VpYXlrSDyQtkPR/ktasMj6zEWYz4G/AWZLukXS0pLWqDsqsl7ggbGYASNoYuAJYobD6cGAdYDzwdeBHFYRmNiJFxN0R8c2I2Bj4GPAB4C5JN0napuLwzHqCC8JmVnMQ8OW6dbsDx0fE0xHxG2AZSROGPzSzkUfJZEnnADcArwe+BHwVmFZlbGa9wg/LmVnNnsAadevGAnMKy/cDawP3DVdQZiPYw8DfgZ8Am0TEfABJS7Fk3plZm7ggbGYARERIql89ClhUWH4GWHHYgjIb2T4UEbfUr4yIl4EdK4jHrOc03DRC0g6Slm5nMGbWcRayZMF3WaDP7p4k7SdptqTZCxYsGJbgzLpZfSFY0oqStqsqHrNeVKaN8KHA3yR9T9Lm7QrIzDrKjcAWAJJGAROB+X3tGBHnRMTEiJi4yiqrDGOIZt1J0j11q54CLqgiFrNe1XDTiIh4v6TVgZ2Ab0r6J1K7ph9HxJ3tCtDMKnUOcLakBcB2wPPA76sNyWzEWL5ueRnghSoCMetVpXqNiIgHgbOBU4EHgK8AV0g6vQ2xmVnFIuJq4AjgeFI3av8cEYurjcqsu0n6sqT7gTGS7qtNpD6Fv9PgMdznt1kLNHxHWNLHgF2BjwJ/BH4MfAJ4AngE+Ld2BGhm5Uh6M/Cv1D3UFhHHDPa7ETEPGFe37gJcXWvWStNIfXb/Dti6sH5hRDw92C/nPr+ns+TNrGKf35NIfX6/t0Xxmo1YZe4IH0MqAP+/iNgmIr4fEYuA0cAX2xKdmTXjSuAjpPxWYTKzDhART+QvnXdFxPzCNGghOHOf32YtUqaN8Mb9rH8ZuLhlEZnZUK0VEX5azazDRcQW/W2TdGZEfKGfze7z26xFynSf9gFJo9sZjJm1xAxJ21YdhJkNySf62xAR0cdq9/lt1oQyA2r8mNTe6G9tisXMWmMeMF3SlcBcYDE01kbYzDpG2eZMtT6/n83LA/b5DewHMHbs2GbjMxsRyrQRPgs4sF2BmFnLPA2cBNwFBG4jbNaN+rrrOxD3+W3WhDJ3hF8P7CppI+CG2srB7jJJWg+4MCLWy8tLkwrVO5DaLu0REfeWDdzM+hYRRyuNlbw26WJ6dz9VqWY2crjPb7MmlCkIB/Bfeb6hu0vu4sVs+OUnxa8gPTwDMF/SJyLCD82YdY9StTgRcbWkWp/fC3Cf32YNKdNrxNFNHL/WxctphXW7AwfnbmJ+I+lkSRN8kTZrmXOAsyPidABJXwC+D0yuNCozK+O3A210n99mrVFqZLkiScvnZg8D2RO4tW5df128mFlrrFsrBANExJmkWhgz6xIR8S9Vx2DWC8p0n/a/dateBn490O8MtYsXSftJmi1p9oIFCxoN1azX3SXpc7UFSfuSHpwzsw4i6RZJ7uLMrEJl7gi/q275JfrpmmUQtS5eavrt4sVPtpo1ZT/gAEmPS3qM1NvLfhXHZGavdS/w/qqDMOtlg7YRlrQXsDfw5rq7wmOBi5o4Z62Ll4sKXbyc0MRxzKwPEXGPpPV5tcnR3Iho5kurmbXXt4Ez813hmbWVEfGX6kIy6y2NPCw3g9QX4XSg+MDcgoi4o4lzuosXszbLBd9m8tPMhs+F+edxhXUBTKggFrOeNGhBOCLmk7pfeioirhvqCd3Fi5mZGUTE+KpjMOt1ZbpPayph3cWLWftJ2jkiLsnze/a1T0ScP7xRmZmZdbaGC8KSJgGHUtfDQ0Rs0+qgzKy0zYBL8vzWfWwPwAVhsw4i6Z3AGaT2/BsBs4CdI+LmSgMz6yFlRpb7CfADUiffHq7VrINExIGF+X2qjMXMGnYe6QvsehGxUNJU0nM0kyqNyqyHlCkILxMR32xbJGZmZr1lTeC7pNpWIuJCSSdVG5JZbynTj/A5ko6WVGr8czMbXpI+3s/65Yc7FjMb0FzgQ+RaVkmfAv5caURmPaZMQXhL4BDgAUkzJP1vH6PNmVn1vi5pvKR31FZIOgx4RNKhFcZlZkvaHzgdeEse/ObIvM7MhkmZphFT2xWEmbXUncANwChJp0bEicCuwHrAL/AANmYdISJul7QOSw5+83KVMZn1mjIF4fvbFoWZtdIHgfHA60iDapwIrBwRf5a0XKWRmdkScsH39qrjMOtVZQrC15HaMY0CVgWWJo045xFwzDrL34F9gWWARZJWBpaVtDTgoZbNOoSkW4AtImJR1bGY9aqmBtSQ9Drgq8BL7QjKzIZkN9Jw6C+Suj2cBfwYuInUNMLMOsO9wPuB/6k6ELNeVeaO8D9ExIvAcZL+h1TtamYdIiLuAXYvrPoWQL4z7DtPZp3j28CZklYEZtZWRsRfqgvJrLeUGVlubN2qCaR2iGbWYSS9H9iA1GH/ThFxYUQsrDgsM1vShfnncYV1gZscmg2bsm2EixYBh7cwFjNrAUlHAHsDKwE/BL4iab2IOKzSwMxsCcUmh2ZWjabaCJtZR9uf1FXabRHxrKTNgbsAF4TNzMwKGh5QQ9IoSYdIuknSLElflVRmQA4zGx4vAM+RR6si9fAS/e9uZlWQtEfuzcXMKlKmIHsCsH3+eSKwHXB8O4IysyGZBlwGvEHSAcCv8zoz6yxHA6tVHYRZLyvTRngX4F0R8SyApGtII1h5yFazDhIRR0vaG3gS+ABwZkScV21UZtaH44FjJO0dEa61MatAmYLwi8AYoNaty8p5nZl1mIiYhu8Cm3W6zYGtgTskzaqtjIhPVxeSWW8pUxA+Dpgl6RJSe8MpuNcIs44jaQ/g4ojwgDdmnW1GnsysImV6jThP0t3ADnnVrhFxY3vCMrMhOJrUOf/8qgMxs/5FxA+rjsGs15UaWS4XfG+UtExEPN+mmMxsaNzu0KxL9DX4TcUhmfWUMt2nTZR0e178jKT5kjZqU1xm1rxiu8Nza1PVQZnZkvLgNxeQmh6OIg1+496YzIZRmTvC3wNOyvNnAQ/ln+9tdVBmNiQzcLtDs27gwW/MKlamIDy21gVTRCwGLpV0envCMrNmDdTuUNKEiLhvOOMxs3558BuzipUZUON2SfvUFiTtBdzd+pDMrI1mVh2Amf3DNDz4jVmlytwR/jxwhaST8/IjwCdaH5KZtZFK/0IaPGcj4JW86jAP0GE2dB78xqx6ZbpPmytpXWBt0sX0roh4BVzdatZFmql23RBYozaqpJm1jge/MatWmaYRRMQrEXFHRNxeKwRnrm41G4EkTQAediHYrDUkzZW0Up7/j6rjMet1pQrCAyhd3WpmXWFTYFVJD0paKOlMSaX6HzezJbwxIh7P8x5K2axirbqg+SlXs+5Q9kvry8AJwH8CKwBXA3sDP3jNgaX9gP0Axo4dO6QgzUawO3O/3vOAFSQdWb9DRBzT7MHdpt+sHN/ZMesBkpaKiJeBncr8XkRMLyw+JmkasB19FIQj4hzgHICJEyf6y7FZ33YCPgW8mXQTqdU1qm7Tb1aCC8JmI4ykKcUCrKRtgVOBd0fErJLH2hX434h4JK9anVfvNJlZSRGxCDgNQNLnI+LoVh3bbfrNyqusjbCkayQtkPRwnvYZ/LfMrAFHSdpV0jhJlwPfBg5s8liTgP+QtLyk9wD7ABe3KlCzHrd9i4/nNv1mJQ2pIFxIsFLVrVmt+mbVPLkNk1lrTAa+CvwfcCWwYURc3eSxjgLeCvwduBA4NiL+uyVRmvW4iPijpPdL2l/SMpJ2H+Iha236xwNrAZuQ2vQvQdJ+kmZLmr1gwYIhntKsuzVcEJY0pW55W+BWgCaqW119Y9YmuRnDZOA+QHlI9GaP9WRE7BARy0XE2hFxRssCNetxko4ALgCOI9WsfkXS8c0eLyKmR8TJEfFSRDxG6p94uz72OyciJkbExFVWWaXZ05mNCGXuCLeyutXVN2YtJGmxpFdqE7CQ1Kzh7Nq2ikM0s9fan3Q9fCEingM2B/Zo9mD5Gv2Wwiq36TcbRJmCcCurW119Y9ZCETEqIkbXTaMK0+iqYzSz13gBeI5XuyBdmqF1R+o2/WYlNVwQbnF1q6tvzNpI0ib55waSJlcdj5n1aRpwGfAGSQcAv2Zowy27Tb9ZSQM2R5C0mNd+OxUwSdLZQDRzp8ldMpm1j6RDgIOBVUkXxbMknR4R36k2MjMrioijJe0NPAl8ADhzKA+OR8STwA4tCs+sJwxYEI6IVnWvVm8SsI2kg4G1SdU3X2zTucx6zQHABgARcY2kTYHZgAvCZh0mIqYxtLvAZjYEpQq6LaxudfWNWfsEsKiw/AwePMes40jaQ9LSVcdh1svKdJ92CPDzvPhW4BxJBzVzUnfJZNZW04ErJO0g6ePApXkys85yNLBa1UGY9bIyd4SXqG4ldflyQDuCMrMhOQS4EfgGcARwE6nHFzPrLMcDx0gqPTqrmbVGmepSV7eadYGIeAk4Nk9m1rk2B7YG7pD0j4GpIuLT1YVk1lvKFGRr1a1nkQrFn8fVrWZmZs2akSczq0iZgvAhwNdI1a0itRf+VjuCMjMzG+ki4of9bZM0ISLuG854zHpRwwVhV7eadS5J0yNiSp6/lj5Gp4qIbYY9MDNr1kz8IJ1Z27mNr9nIcHJhfmpVQZhZy/gBOrNh4IKw2QgQEcUHba6rMhYza4nX1OqYWesNNsSyq1vNzMzMbEQa7I6wq1vNzMzMbEQasCDs6lYzM7NKuI2w2TBwG2GzEUDSnoPtExHnD0csZtY8SUtFxMvATlXHYtYLXBA2Gxm2HmR7AC4Im3UQSVMiYnpheVvgVODdxRpZM2sfF4TNRoCI2KfqGMystKMkLQXcRCoATwAOrDYks94yWK8Rrm41MzNrj8nAL4DVSaO2nhsRi6sNyay3DHZH2NWtZl1G0hjg6Ij4oqTdgO2BAyNiYcWhmVlBRDwiqVYYlgvBZsNvsF4jXN1q1n3OBf6e52cCmwLfxw/fmFVO0mJe2ye/gEmSzgYiIkYPf2RmvclthM1GnknA2wAi4gFJBwMPVhvSa73nq65MasScbw/aQs26SESMqjoGM3tVwwkpaYykM/L8bpIukLRy+0IzsyY9CqxTWF4HeKKiWMxsAJI2yT83yM0kzGwYlflmei7wujw/k3Sx/X7LIzKzoToUuE7SZZIuBa7L68ysg0g6BPh5XnwrcI6kgyoMyaznlGka0RXVrWa9LiKulDQJ+DCp7eEhEXFvxWGZ2WsdAGwAEBHXSNoUmA18p9KozHpImYJwrbr1trzs6lazDpULvi78mnW2ABYVlp/Bz+6YDasyCVerbr2elLxbAO5VwszMrDnTgSsknUW6rn4euLTakMx6S8MFYVe3mpmZtdQhwNdIg2mI1F74W5VGZNZjSlXBuLrVzMysNSLiJeDYPJlZBdyfoZmZmZn1JBeEzczMzKwn+elUMzOzYSJpekRMyfPX8trhlomIbYY9sAF4FMjGeSTI7uOCsJmZ2fA5uTA/taogzCxxQdjMzGyYRMSswvx1VcZiZm4jbGZmZmY9ygVhMzMzM+tJlRWEJW0l6U5JD0k6oqo4zGxwzlez7uBcNSunkjbCklYCLgM+QxpJ52pJv4+IX1YRj5n1z/lq1jqSBu1WICKa6qbBuWpWXlUPy20P3BcRlwJIOg3YHXCymnUe56tZ62w9yPYAmu2vzLlqVlJVBeGxwJzC8n3A2hXFYmYDc76atUhE7NPGwztXzUqqqiA8ClhUWH4GWLF+J0n7AfvlxaclzR2G2OxVY4BHqw6iG+ikvVp1qDVadaAW6qV87bj3fAvfW52q4/7mHKVG9+y0fO2lXIUOfO84XyvQWL72m6tVFYQXsmRQywKv1O8UEecA5wxXULYkSbMjYmLVcVjleiZf/Z4ffr38N5c0Bjg6Ir4oaTdS04YDI2Jhk4fsmVyF3n7vVGUk/s2r6jXiRmCLwvIkYH5FsZjZwJyvZu1xLvC6PD+TdKft+0M4nnPVrKRKCsIRcSvwmKQTJU0GDgd+XEUsZjYw56tZ20wCPgcQEQ8AB+d1TXGumpVX5YAaOwFvI427fmZE/KjCWKxvXV91Zi3TK/nq9/zw6+W/+aPAOoXldYAnhnjMXslV6O33TlVG3N9cEVF1DGZmZj1H0seAHwLXk7pN2wLYJyJ+XmlgZj3EBWEzM7OKSFoT+DAg4OqIuLfikMx6igvCZmZmZtaTqmwjbGZmZmZWGReEzcxs2ClZR5JHPjPrMJKWlfQ1Sd+TtIekUXXbp1cVW6u5IGxmPUvS6ySt2s+29w53PCOZpFsL85sB9wMzgNsk/VFSp43SZtbLpgE7AI+QuvW7RdKGhe3vryKodnBB2Mx6kqQdgQXAXyXdI2mXul0urSCskWxMYf504PCIeAvwJlKvCadWEpWZ9eXjwPYRcWREvAc4BfiVpM/k7Q2PQ97p/LCcASDpFmD5/jYDEREThjEks7aSNA84DLgY+BjwLeBWUvdVz0h6KCLeVmGII4qkv0XEann+0YgYU9i2AnB/cZ1Zja9Pw0/S34EPR8TNhXVrA5cDvwY+GRFvrSq+Vvr/7d1fyJ5zHMfx90eTZcWKg1HIWjngQP4ViZUTUsgsB8gaW9qBHXBgESlTCuXPAfmTHTFJZiP/DiZq5mlPa5SWmRGl/FkOlL/7OriuZ9174sDjuf9e71fd9Vy/333ffa966ve9f9f1/V4Lhh2ARsYNNP/gtwOfDjkWaRCWAK9X1V/AliRvA48DU0muounrqvmzOMlGYAr4IcmynlZhS4FfhheaRpzr0+DdC7yaZGVVTQNU1d4kFwFvcOQVnrHmjrAOS3IOsL6qbh52LFK/JXkP2FlVd88aXwfcDxxbVYuGEtwESnIhcC5wPnABsKOqVie5FngKWFdVE1OAo/nl+jR4Sc4HfquqPbPGFwBXTMqDX0yEJXVSWyT3DPBKVW2aNXcVcF97b5zmQZJjgfXAacAHwItVdSjJycCfNI8Dvm6YMUrqHhNhSVLfJXkZOAV4F7gSOAa4sap2t/OH7yGWpEExEZYk9V2SX4GTqupge7waeAi4q6qeszhR0jDYPq0jklyf5LE5fG55ku19CEkaqiR7kuz/l9eXSfYPO8YJ8zNw6sxBVT0PXAzcmeQJXI80ZlxXJ4NdIzqiqjYDm4cdhzRCrEQfrM5UoasbXFcng4mwpE6qqk+SrKSpRH9j2PFMuqp6Osk0TWFc7/jBJJcAVwwnMkld5qWojkiyKskLPcfbk9yWZCrJj0k29cytaC8Nfw6s7BlfmOTJJN+0rzXt+HFJvk5yaXu8Nck9gzs7aW6qatp2TINTVVOzWzG1439OSismdYfr6mRwR7jb7gAuB34C9rbPEf+O5hnjlwG7gW09798ALAKW0TyMYFeSd6vqQJK1wBNJNtBUhl87sLOQJGk0uK6OGXeEu+3RqvqireL+DFhM0+h+X1V9XFW/0zS6n3ElcDVwAPiI5ofUWQBV9RYwDbwE3FJVfwzsLCRJGg2uq2PGRLjb9vb8PdNH7yjgUM/4X7M+s7qqllTVEppfqO/1zJ3Qvn/xfAcqdYWV6NJYc10dMybC3XboH8amgDOSnJ3kaGBNz9ybwJr2nqYTaX7tngfQ3td0PE3By7NJju9v6NJkqqrNVbV+2HFImhPX1TFjIqwjVNW3wFpgC7AP+L5n+kHgq3Z8F/BIVX2Y5HRgPr+FaAAAAOBJREFUI3BrVe0AtgL/eUdLkqRJ47o62nyynCSNkCSrgOVVtao93k57jyCwFNg20+kiyQrgYZqWZO8AZ1bV8iQL2/Fr2q+9v6qeSXIcTc/km6rq/SRbgZ1V9cCgzk+SRoldIyRp9FmJLkl94K0RkjT6rESXpD5wR1iSRt9cK9Ffg6Y5P/B7z5yV6JKEO8KSNA6sRJekPjARlqQxZCW6JP1/do2QJElSJ7kjLEmSpE4yEZYkSVInmQhLkiSpk0yEJUmS1EkmwpIkSeokE2FJkiR1komwJEmSOslEWJIkSZ30Ny/x8TGSABF0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分析用户点击环境变化是否明显，这里随机采样10个用户分析这些用户的点击环境分布\n",
    "sample_user_ids = np.random.choice(tst_click['user_id'].unique(), size=10, replace=False)\n",
    "sample_users = user_click_merge[user_click_merge['user_id'].isin(sample_user_ids)]\n",
    "cols = ['click_environment','click_deviceGroup', 'click_os', 'click_country', 'click_region','click_referrer_type']\n",
    "for _, user_df in sample_users.groupby('user_id'):\n",
    "    plot_envs(user_df, cols, 2, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看出绝大多数数的用户的点击环境是比较固定的。思路：可以基于这些环境的统计特征来代表该用户本身的属性"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 用户点击新闻数量的分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:40:04.296033Z",
     "start_time": "2020-11-13T15:40:03.980868Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x20d488b4470>]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "user_click_item_count = sorted(user_click_merge.groupby('user_id')['click_article_id'].count(), reverse=True)\n",
    "plt.plot(user_click_item_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以根据用户的点击文章次数看出用户的活跃度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2339d302b00>]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#点击次数在前50的用户\n",
    "plt.plot(user_click_item_count[:50])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "点击次数排前50的用户的点击次数都在100次以上。思路：我们可以定义点击次数大于等于100次的用户为活跃用户，这是一种简单的处理思路， 判断用户活跃度，更加全面的是再结合上点击时间，后面我们会基于点击次数和点击时间两个方面来判断用户活跃度。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x233a04386a0>]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#点击次数排名在[25000:50000]之间\n",
    "plt.plot(user_click_item_count[25000:50000])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看出点击次数小于等于两次的用户非常的多，这些用户可以认为是非活跃用户"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 新闻点击次数分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:42:14.526476Z",
     "start_time": "2020-11-13T15:42:14.463642Z"
    }
   },
   "outputs": [],
   "source": [
    "item_click_count = sorted(user_click_merge.groupby('click_article_id')['user_id'].count(), reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-13T15:42:16.198000Z",
     "start_time": "2020-11-13T15:42:16.044455Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x20d48b0eda0>]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(item_click_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x233a04f5a90>]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(item_click_count[:100])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看出点击次数最多的前100篇新闻，点击次数大于1000次"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x233a0551d30>]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5dxWQAIwHqoCjR/qkB5831Nrxzz3XOed3zvmzs7Nb057EgM+P6s2Y/G787qUNVNXWe92OSExqcQCY2X1mdnbwZjdgP1AMFAZrBUBJC2oin2Jm/PziEZQfrOVPr2/yuh2RmNSana9/CzxiZg54yTm3wczmAwvNbDIwAnibwKqeUGoiJzQ2P5NLCvowd8lmZp+Zr9NJiIRZyEsAzrkpwd9bnHOFzrnJzrlfBWulwFRgGXC+c64h1Fp4347Emh9dOBSA3/1rvcediMSesJ2UxTn3sXNuQdMNxqHWRE6mb2YqcyYP4KlVH7OqbL/X7YjEFJ2VSyLedVMG0yM9iV89t1YXnxcJIwWARLz0pHhunHYaxaX7WLh6p9ftiMQMBYBEhSv8eQzrlcF/vbBOVxsTCRMFgESFOJ9x8/QRbNt3iIffLPG6HZGYoACQqFE4pAfnDevJPa9u1IXnRcJAASBR5afTh3P4SAO/X/Sh162IRD0FgESVQdnpfHlCPx5bsZUNO9vtUhQinYICQKLOd88bQnpSPLcuXOd1KyJRTQEgUSczLZH/d94QlnxYzmsbdnvdjkjUUgBIVPrqxP70757Krc+vo76h0et2RKKSAkCiUmK8j598bjgbd1fx2IqtXrcjEpUUABK1po3IYcLALH7/8kccOHTE63ZEoo4CQKKWWeDgsH01ddz72kav2xGJOgoAiWpn5Hbl8rF9eXhZCaV7q71uRySqKAAk6t14wVDi44zfvKBrBoi0hAJAol5Ol2S+dc4gXvhgJyu2VHjdjkjUUABITPjG5IH07prMr55bS2OjrhkgEgoFgMSElMQ4fnThUFZvP8BTq7Z73Y5IVAgpAMwsx8yWBqfzzWyxmb1qZnMtIMHMnjWzZWZ2TXBcSDWRcJlRkMuovl357b82UFNX73U7IhGv2QAws0xgPpAWLH0TuM4591kgDxgJ3AAUO+cmAZebWUYLaiJh4fMZP794BDsrD/PnJVu8bkck4oWyBNAAzAIqAZxzP3POHT0LV3dgDzAFWBCsLQH8Lagdw8yuNbMiMysqLy9v2buRTm98/yw+N7IX97++ic3lVV63IxLRmg0A51ylc+7A8XUzmwWscc59TGDp4OiK1wogpwW1419vrnPO75zzZ2dnt/DtiMBPLhpOUoKPGfcs44XVO7xuRyRitWojsJkNBG4EvhcsVQEpwen04POGWhMJq7ysVJ67oZCBPdO57m/v8J/PrKGuXieMEzleiz+Ag9sEHgOuabJkUAwUBqcLgJIW1ETCrm9mKk98cyLXTBrAw2+WcMX9b1JWUeN1WyIRJb4Vj7kJyAfuNjOAXxDYSLzQzCYDI4C3CazqCaUm0i4S4338x+dHcOaALH745HtMv2spt19RwLTTe3ndmkhEMOfCc9CMmfUh8O3+xaNLBqHWTsbv97uioqKw9Ced29a9NXzn0XdYvf0AcwoH8OOLhpEQpzWQEpvMrNg596mdbD41LlwB0B4UABJOtfUN3Pr8Ov7yVilj8rtxz5Vjye2W0vwDRaJMqAGgr0DSaSTFx/HLGWdwz5Vj+GhXFdPvWsqr63d53ZaIZxQA0ulcPKoPz95QSJ+uKVzzcBG/eWG9LispnZICQDqlAT3S+Oe3z+LKz+Rz/+ub+OKfl7PzwGGv2xLpUAoA6bSSE+K47dKR/HH2aNZ8XMnn7lrK6x/q6HPpPBQA0unNGJ3LM9cXkp2exNUPreCOlzbQoFNKSyegABABBvdM56nvTOKKcX25+9WNfOmB5eyvqfO6LZF2pQAQCUpJjOO3lxdwxxUFFJfu48f/eJ9I3k1apK0UACLH+cK4vvzwgqG8uGYXTxRv87odkXajABA5gTmFA5kwMItbnlnD1r06h5DEJgWAyAn4fMYdM0fj8xnfX7BKxwlITFIAiJxEbrcUfv1vZ1Bcuo/7Fm/yuh2RsFMAiJzCjNG5XFLQhz++8hHvle33uh2RsFIAiDTjVzPOIDsjie8/vkoXm5eYogAQaUbX1ATumFnAlr3V3LZwXfMPEIkSCgCREJw1qAdzCgfw1+VbdQZRiRkKAJEQ3XjBUIb1yuBHT77Pnqpar9sRaTMFgEiIkuLj+MPs0VQequemf6zWUcIS9UIKADPLMbOlTW4PN7Onm9zuZmZLzGyZmV3UkppINBnWqws/unAoL6/bxeMry7xuR6RNmg0AM8skcNH3tODtQcDvgK5Nhv0SeBA4G/iRBa4WH2pNJKpcM2kAkwZ355fPraVkT7XX7Yi0WihLAA3ALKAyePsg8IXjxpwNPOmcawA2AP1bUBOJKj6fcfsVBcT7jO89rqOEJXo1GwDOuUrn3IEmt3c7547fAlbvnKsKTlcAOS2oHcPMrjWzIjMrKi/XxTkkMvXumsKtl45kVdl+7nlto9ftiLRKuDYCNzSZTg8+b6i1Yzjn5jrn/M45f3Z2dpjaEwm/zxf04dIxudz96kbe3brP63ZEWixcAbDGzPzB6QKgtAU1kah1y4zT6dUlme8/vorqWh0lLNElXAFwHzDPzOYCB51z21tQE4laXZIDRwmXVtTw6+d1lLBEl5ADwDk35WS3nXMrCWwYfin4O+SaSLSbMLA71549kMdWbGXRWh0lLNEjPlxP5JzbCGxsTU0k2v1g6mks/XAPN/3jfUbnnU12RpLXLYk0S0cCi4TB0aOED9bW61rCEjUUACJhclpOBj+5aBivrt/Noyu2et2OSLMUACJhdNXE/kwe0oNfPbeWjbsPet2OyCkpAETCyOczfnd5AWmJ8VzzcBF7ddZQiWAKAJEw69U1mT9f5WdX5WGufaSYw0camn+QiAcUACLtYGx+Jr+fNZri0n3c+MR7NDZqo7BEHgWASDv53Mje3HTRMJ57fwd3LvrQ63ZEPiVsxwGIyKd98+yBlO6t5p7XNpLfPZWZ/jyvWxL5hAJApB2ZGb+ccQbb9h3ip/9cTd9uKZw1uIfXbYkAWgUk0u4S4nzc+6WxDMxO45t/LdbuoRIxFAAiHaBLcgLzrhpPUnwcVz+0kvKD2j1UvKcAEOkgeVmpPHCVnz1VtXzjL0XaPVQ8pwAQ6UCj87rxh1ljeG/bfn6wYJV2DxVPKQBEOtiFZ/TipxcNZ+Hqnfz2xQ1etyOdmPYCEvHAnMkDKNlbzf2vb6Jf91S+eGa+1y1JJ6QAEPGAmXHLJaezbd8hbn7qA/pmpjB5iK6BLR1Lq4BEPBIf5+OeK8cwpGc63/7rO2zYqd1DpWMpAEQ8lJGcwINXjyclMY5rHl7J7oOHvW5JOpGQAsDMcsxsaXA6wcyeNbNlZnZNW2sinV2fbinMu2o8FdV1zJlfxKE67R4qHaPZADCzTGA+kBYs3QAUO+cmAZebWUYbayKd3si+Xbnri2NYvf0A33v8XRq0e6h0gFCWABqAWUBl8PYUYEFwegngb2PtGGZ2rZkVmVlReXl5yG9EJNpNHZHDz6eP4MU1u/jNC+u8bkc6gWb3AnLOVUJgr4WgNGB7cLoCyGlj7fjXmwvMBfD7/foaJJ3K1yb1p3RvNX9euoVN5dV8bVJ/Cgf3aPr/TyRsWrMbaBWQAhwA0oO321ITkSAz4+cXjyArLYm/vFXCV+atYEjPdK46qz+Xjc0lNVF7bkv4tGYvoGKgMDhdAJS0sSYiTcTH+fju+UNYdtNnuf2KAhLjfdz81AdMuO0Vblu4jrKKGq9blBjRmq8T84GFZjYZGAG8TWC1TmtrInICyQlxXD6uL18Ym0tR6T4eXlbCvDe28MDSzUwdkcPVZw1gwsAsrR6SVjPnWr6a3cz6EPgm/6Jz7kBbayfj9/tdUVFRi/sTiVUf7z/EI8tLeWzFVvbXHGFYrwy+Nqk/M0bnkpwQ53V7EiHMrNg596mdbD41rjUB0FEUACIndvhIA0+v2s5Dy0pYv/Mg3VIT+OKZ+XxlQj/6dEvxuj3xmAJApBNwzrF8cwUPv7mFRWt3YWZceHovvjqxH8N6dSE1KY6EOB3w39mEGgDapUAkipkZEwd1Z+Kg7pRV1PDI8lL+vmIrz6/e8cmYxDgfqUlxpCXGk5oYF/yJJy3p2N/H1zOS4+mSnECXlMDvrqkJpCfG4/Npm0Os0BKASIypqatn0dpd7Kmqo6a2nuq6Bmrq6qmubeDQkcDvo7dr6oL319ZTc6SB5j4OzCAjKZ4uKQnHhMPxt7umJNCnWwr9e6SSk5Gs0OhgWgIQ6aRSE+OZMTq3xY9zznH4SCPVdfVU19Zz8HA9lYeOUHn4CJWH6oO/j1B5XH1rRc0n9ara+k89b1K8j37dU+nXPY3+n/xOo1/3VPp0SyFO4eAZBYCIAIHVSSmJcaQkxtEjPalVz1Hf0EhVbT37a46wbd8hSvZWs7WihpI91ZTurWHJh+XU1jd+Mj4hzsjLSv0kEPplpdKvRzAgslK15NDOFAAiEjbxcT66pSbSLTWR/j3SKBzS45j7Gxsduw/WUrK3mtK91ZTsrQn83lPD25v3Ut3kTKg9M5I4b3gOU0f05KxBPbSbaztQAIhIh/H5jF5dk+nVNZkJA7sfc59zjj1VdZTurWbj7iqWfFTOM6u289iKraQkxFE4pAdTh+dw7rCeZGe0bglFjqWNwCISsWrrG1i+uYJX1u3i5bW7+PjAYcxgTF43zh+Rw/nDcxjSM11HQx9HxwGISExxzrF2RyUvr93NK+t38f62wIkE8rNSOX94DueP6Mn4/lk67gEFgIjEuJ0HDvPK+sCSwbJNe6mrb6RLcjxThvbk/BE5TBmaTZfkBK/b9IQCQEQ6jZq6epZ+tIeX1+7i1fW72VtdR0KcMWFgd6aOyGHqiBx6d+08p8hQAIhIp9TQ6FhVto+X1u5i0ZpdbN5TDcDI3K5MG5HD1NNzGJqTEdPbDRQAIiLAxt1VvLR2J4vW7uLdrfuBwHaDo0sG/n6ZxMfYdgMFgIjIcXZXHubldbtZtHYnyzbupa6hkczUBD47LIdpp+dw9pBsUhKj/3gDBYCIyClU1dbz+oZyFq3dySvrd3PwcD1J8T4mD8lm2ogcLji9F11To3MjsgJARCRERxoaWbGlgpfWBFYVfXzgMEnxPqaP7M0XP5OPv19mVG0zUACIiLSCc473tx1gQVEZT6/6mKraegb3TGf2+Dy+MLYvmWmJXrfYrHYLADMbANwDdAFWOOf+3czmEbjG7/POuV8Hx4VUOxUFgIh4qbq2nuff38GjK7ayqmw/iXE+LjyjF7PPzGPiwO4Ru1TQnqeD/m/gV8655Wb2uJldBsQ55yaa2YNmNgQYGUrNOfdRK15fRKRDpCXFM3N8HjPH57F+ZyV/X1HGP9/ZxjPvfUz/7qnMPjOfy8f1bfXZU73WmiWAVcCZzrk6M7sbuBj4jnNuoZnNBlKAMcC/mqs55x461WtpCUBEIs3hIw0sXL2Dv68oY0VJBfE+Y9rpOcwen0/h4B4RcQrr9lwCeBL4hZktBy4EXgW2B++rAMYCaSHWTtT4tcC1APn5+a1oT0Sk/SQnxHHZ2L5cNrYvG3cf5O8ryvjHO9tYuHoneVkpzPLncYU/j5wuyV632qwWH/0QXHf/AjAHmA9UEfiGD5AefM5Qayd6/rnOOb9zzp+dnd3S9kREOszgnhncfPEIlv/0PO764hjyMlO5/aUPOes3r/Lr59ZS1+TiN5GotYe/rQLygTuBYqAwWC8ASlpQExGJeknxcVxS0IdHvzGBxTdOYaa/Lw+8sYWZf3qLbftqvG7vpFq1G6iZ3QJsdM49YmZdgKXAK8BFwATAhVJzzh041etoG4CIRKuFq3fw4yffx+cz7pxZwHnDczrstTv0OAAzywSmAkuccztbUjsVBYCIRLOSPdV8+2/vsHZHJd88eyA3XjC0Q65XoAPBREQiwOEjDfzqubX87e2t+PtlcveVY9r91NShBkBsnQJPRCTCJCfEceulI/nj7NGs21HJ5/64lMUbdnvdFqAAEBHpEDNG5/LMDYXkdEnm6odW8rsX11Pf4O1eQgoAEZEOMig7nae+M4nZ4/O497VNfOmBt9lVedizfhQAIiIdKDkhjt98YRR3zizg/W0HmH7XUt74aI8nvSgAREQ8cNnYvjxz/SQyUxP5yoNv8/tFH9LQ2LE75SgAREQ8MiQng6evn8RlY/ryx1cagn8sAAAFR0lEQVQ+4qsPvk35wdoOe30FgIiIh1IT47ljZgG/vXwUxaX7+NxdS3lr094OeW0FgIhIBJjpz+Pp7xSSkRzPlx5YzoNvbGn311QAiIhEiKG9Mnj2+kJmjM5lQI+0dn+91pwOWkRE2klaUjy/nzW6Q15LSwAiIp2UAkBEpJNSAIiIdFIKABGRTkoBICLSSSkAREQ6KQWAiEgnpQAQEemkIvqSkGZWDpS28uE9AG/OsRqaSO8PIr9H9dc26q9tIrm/fs657OYGRXQAtIWZFYVyTUyvRHp/EPk9qr+2UX9tE+n9hUKrgEREOikFgIhIJxXLATDX6waaEen9QeT3qP7aRv21TaT316yY3QYgIiKnFstLACIicgoKgHZkZl3N7AUze8nM/tfMEk8wJt7MtprZ4uDPSC96jURmdl2T+bLKzP50gjGafydhZjlmtjQ4nR+cP6+a2Vwzs5M8JtfMtjWZn83uShirjpt/tzSZJ+vN7CcneUx0zT/nXFT/APOAt4Cb2zKmnXr7NjA1OH0fcMkJxowF/tujeRcPbAUWB39GnmTcLcBK4F4P/53vBvwRNv9ygKXB6QTgWWAZcM0pHhPSuDD0lgn8C3gnePtWYHhw+gVg1EkedxlwnQfzLxfY1uRvMfsUj2v3/8/Hz7/j7nsSyPV6/oXjJ6qXAMzsMiDOOTcRGGhmQ1ozpr045/7HObcoeDMb2H2CYROAi81shZnNM7OOvErbKOAx59yU4M/q4weY2TigEDgT2G1m53dgf0d7yAVynHNFJ7jbk/lnZpnAfODodftuAIqdc5OAy80s4yQPDXVcWzUAs4BKAOfcz5xz64L3defkBzBNAOaY2Ttmdls79Xai+fcZ4NYmf4vlJ3lcR/1/Pmb+NXn98cA259z2kzyuQ+ZfuER1AABTgAXB6ZcIfFC1Zky7MrOJQKZzbvkJ7l4JnO+cO5PAt8PPdWBroXx4ngP8wwW+3rwITO7A/o76DoElqBPxav4d/wExhf/7O1sCnOwAoVDHtYlzrtI5d+D4upnNAtY45z4+yUNfCPY4HphoZqPaoz8+Pf9C/eCcQgf8fz7Z/AO+S2Bp9GQ6av6FRbQHQBpwNIkrCCxStmZMuzGzLAJ/MNecZMj7zrkdwekioMOWUAjtw9Pr+ecDziWwWuBEPJl/J/iACHU+eTY/zWwgcCPwvVMMe9M5d9A51wC8SzvNzxPMv1A/OL2cf92Ans65TacY1iHzL1yiPQCqgJTgdDonfj+hjGkXwY2+TwA/cc6d7JxGj5hZgZnFAf8GvNdR/RHah6dn8y9oMvB2cAnkRLycf02FOp88mZ/BVS6PEdjucKJvtke9aGa9zSwVmAZ80BH9EfoHp5d/jzOAhc2M8Wr+tUq0B0Ax/7cIWACUtHJMe/k6gY2UPwvuEfALM/v1cWN+CTwCrALecs693IH9hfLh6eX8A7iAwKoSzGxEhM2/pkKdT17Nz5uAfODu4N/iOWb2WTO7/rhxtwCvAcuB+51zGzqov1A/OL38e/zkbxEgwuZfq0T1gWBm1gVYCrwCXATMBq5wzt18ijETmvkG1GmY2RnAo4ABzwB3AL91zs1pMsZHYP4VARcCFzrntnjQbkQys8XOuSlm1o/At8OXgbMIrNM+BxjhnLunyfhPjQt+6+2Umsy/cwls56kD5jrn7jGzEcCV+v/cfqI6AOCTRdupwBLn3M7WjpGTM7MUYDqBXeI2e91PpDKzPgS+nb54qg+lUMfJien/c/hEfQCIiEjrRPs2ABERaSUFgIhIJ6UAEBHppBQAIiKdlAJARKST+v89l5PF0jAFqQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(item_click_count[:20])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "点击次数最多的前20篇新闻，点击次数大于2500。思路：可以定义这些新闻为热门新闻， 这个也是简单的处理方式，后面我们也是根据点击次数和时间进行文章热度的一个划分。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x233a0591be0>]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(item_click_count[3500:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以发现很多新闻只被点击过一两次。思路：可以定义这些新闻是冷门新闻"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 新闻共现频次：两篇新闻连续出现的次数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>433597.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.184139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>18.851753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2202.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               count\n",
       "count  433597.000000\n",
       "mean        3.184139\n",
       "std        18.851753\n",
       "min         1.000000\n",
       "25%         1.000000\n",
       "50%         1.000000\n",
       "75%         2.000000\n",
       "max      2202.000000"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmp = user_click_merge.sort_values('click_timestamp')\n",
    "tmp['next_item'] = tmp.groupby(['user_id'])['click_article_id'].transform(lambda x:x.shift(-1))\n",
    "union_item = tmp.groupby(['click_article_id','next_item'])['click_timestamp'].agg({'count'}).reset_index().sort_values('count', ascending=False)\n",
    "union_item[['count']].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由统计数据可以看出，平均共现次数2.88，最高为1687。\n",
    "\n",
    "说明用户看的新闻，相关性是比较强的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2339ce36780>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#画个图直观地看一看\n",
    "x = union_item['click_article_id']\n",
    "y = union_item['count']\n",
    "plt.scatter(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2339cc8f908>]"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(union_item['count'].values[40000:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大概有70000个pair至少共现一次"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 新闻文章信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x233e7abf278>]"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAD6CAYAAABOIFvoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAG1lJREFUeJzt3Xt0nHd95/H3Z2Z0sxQ7vsiO7VxN3AaK7aVRLgaHCDAhAdplc7pNz9ItZ2mO2SwL3UvPAoVz2LAk9PTCOZRCwW26m2bbdAMUlluOE05jYhJMLOdOQsIm2Ikdh8iWb7JlSxp99495JI9kjTwaaTQzfj6vc+b40Xeemfn9/Gj0md/ze555FBGYmZkBZGrdADMzqx8OBTMzG+NQMDOzMQ4FMzMb41AwM7MxDgUzMxvjUDAzszEOBTMzG+NQMDOzMblaN2C6lixZEhdffHGtm2Fm1lB27ty5PyI6z7Rew4XCxRdfTE9PT62bYWbWUCTtLmc97z4yM7MxDgUzMxvjUDAzszEOBTMzG+NQMDOzMQ4FMzMb41AwM7MxqQmF5149yp/f9xwH+k/WuilmZnUrNaHwYm8/X/zn/0evQ8HMrKTUhEJrUxaAE0MjNW6JmVn9Sk0otOQKXT0xlK9xS8zM6ldZoSBpmaRtyfKtkrYmt59J+oSklZL2FNU7k3XvkPRjSZ8qeq6yarOtZWyk4FAwMyvljKEgaSFwJ9AOEBGfjojuiOgGngb+DrgKuG20HhG9km4EshGxHlglaXW5tWp0tLVpdKTg3UdmZqWUM1LIAzcBR4qLkq4A9kTEXuBq4GZJj0q6PVmlG7gnWb4P2DCN2jiSNknqkdTT29tbVscmGp1TODnskYKZWSlnDIWIOBIRhye56w+ALybL91L4434FsF7SWgoji73J/X3AsmnUJrZhc0R0RURXZ+cZvw58UmOh4JGCmVlJFV1PQdK5wNKIeCEpPRwRJ5P7HgNWA/1AW3J/B4UAKrc261pHJ5o9UjAzK6nSP8D/Evh+0c9bJC2XNA+4jsJcw05O7QpaB+yaRm3WtXqi2czsjCq98tq7gD8r+vlW4AFgEPhKRDwnaR+wTdIK4AYK8w5RZm3WnTok1buPzMxKKTsUkqONRpf/zYT7HgAum1A7IqkbeCfwJ6PzEuXWZlsumyGXkUcKZmZTqOo1miPiIKeOLJpWrRpam7IeKZiZTSE1ZzRD4VwFTzSbmZWWqlBoyWW9+8jMbAqpCoXWpozPUzAzm0LKQsEjBTOzqaQuFE4Oe6RgZlZKqkKhJZfxSMHMbAqpCoXWpqyPPjIzm0LKQiHj8xTMzKaQrlDwIalmZlNKVSi0+IxmM7MppSoUCucpeKRgZlZKykLBE81mZlNJVyjksgzlg/xI1LopZmZ1KVWh0NI0ek0FjxbMzCaTqlAYvSSnz2o2M5tcukLBl+Q0M5uSQ8HMzMakLBR8nWYzs6mUFQqSlknaliyvlLRH0tbk1pnU75D0Y0mfKnpcxbVqaMoWujs84lAwM5vMGUNB0kLgTqA9KV0F3BYR3cmtV9KNQDYi1gOrJK2eSa0aHQXIZgTAsA9JNTObVDkjhTxwE3Ak+flq4GZJj0q6Pal1A/cky/cBG2ZYq4pcJhkp5B0KZmaTOWMoRMSRiDhcVLqXwh/yK4D1ktZSGEXsTe7vA5bNsDaOpE2SeiT19Pb2lt25iU6NFLz7yMxsMpVMND8cEUcjIg88BqwG+oG25P6O5HlnUhsnIjZHRFdEdHV2dlbQ5IKmbCEUfEazmdnkKgmFLZKWS5oHXAc8Dezk1G6fdcCuGdaqwnMKZmZTy1XwmFuBB4BB4CsR8ZykfcA2SSuAGyjMO8QMalUxOqeQ95yCmdmkyh4pRER38u8DEXFZRKyNiL9MakcozDNsB94WEYdnUpulvp3GIwUzs6lVMlKYVEQc5NRRRDOuVUPOcwpmZlNK1RnNPvrIzGxqqQqFXMYjBTOzqaQqFDynYGY2tVSFgs9oNjObWqpCITu2+8hzCmZmk0lVKIye0ezdR2Zmk0tVKGQ90WxmNqVUhcLYnIJDwcxsUqkKBY8UzMymlqpQGD1PwUcfmZlNLlWhkMkIyUcfmZmVkqpQgMJowXMKZmaTS10oZB0KZmYlpS4UcpmM5xTMzEpIXyhk5TkFM7MS0hcK3n1kZlZS6kIhm5HPUzAzKyF1oZDLZDxSMDMrIXWh4JGCmVlpZYWCpGWStiXLF0raKumfJW1WwUpJe5L6Vkmdybp3SPqxpE8VPVdZtWrxnIKZWWlnDAVJC4E7gfak9CHgloh4O3ABsAa4CrgtIrqTW6+kG4FsRKwHVklaXW5t9rt5SmGk4KOPzMwmU85IIQ/cBBwBiIhPRsSzyX2Lgf3A1cDNkh6VdHtyXzdwT7J8H7BhGrVxJG2S1COpp7e3t9y+TSqbkc9TMDMr4YyhEBFHIuLwxLqkm4CfRsQrwL0U/rhfAayXtJbCyGJvsnofsGwatYlt2BwRXRHR1dnZWX7vJpHLeveRmVkpuUoeJGkV8IfAxqT0cEScTO57DFgN9ANtyf0dFAKo3FrV+OgjM7PSpv0HOJljuBv4YNEIYouk5ZLmAdcBTwM7ObUraB2waxq1qsl5TsHMrKRKRgofBy4EvigJ4NPArcADwCDwlYh4TtI+YJukFcANFOYdosxa1XhOwcystLJDISK6k38/BnxsklUum7D+EUndwDuBPxkdVZRbq5ZcVpwc8kjBzGwyFc0plCsiDnLqyKJp1aolm8kwPJKfi5cyM2s4qTujOeczms3MSkpdKPgiO2ZmpaUuFHz0kZlZaakLBY8UzMxKS10o5HxIqplZSekLhWzGE81mZiWkLxQyYthzCmZmk0pdKPgiO2ZmpaUuFHyRHTOz0lIXCtlMhrwnms3MJpW6UPD1FMzMSktdKHhOwcystNSFgo8+MjMrLXWhkM2IkYARjxbMzE6TulBoyha67HkFM7PTpS4UshkBeF7BzGwSqQuFXBIKnlcwMztd6kLBIwUzs9LKCgVJyyRtS5abJH1H0kOSPliNWjWdGik4FMzMJjpjKEhaCNwJtCeljwA7I+ItwG9JOqcKtarJZgpd9kjBzOx05YwU8sBNwJHk527gnmT5QaCrCrWq8UjBzKy0M4ZCRByJiMNFpXZgb7LcByyrQm0cSZsk9Ujq6e3tLa9nJYzNKfj7j8zMTlPJRHM/0JYsdyTPMdu1cSJic0R0RURXZ2dnBU0+JZf10UdmZqVUEgo7gQ3J8jpgVxVqVZPL+OQ1M7NSchU85k7g+5KuAd4A/ITC7p/ZrFXN6O4jX6fZzOx0ZY8UIqI7+Xc38E7gIWBjRORnuzZ73TtdzucpmJmVVMlIgYh4hVNHDFWlVi3ZZE5hyHMKZmanSd0ZzRctmocE339yX62bYmZWd1IXCqs6O7ip6wL+18O7eOnA8Vo3x8ysrqQuFAD+08ZfYSSCr+18udZNMTOrK6kMhfMWtLJhdSf/9OheX2zHzKxIKkMB4MY3rWTvoQEe33Oo1k0xM6sbqQ2F13V2AHCgf7DGLTEzqx+pDYWWpkLXTw5X9bQIM7OGkt5QyCWhMOTzFczMRqU4FLIAnBx2KJiZjUpxKHj3kZnZROkNhWROYdAjBTOzMakNhebs6EjBoWBmNiq1oZDLZshl5N1HZmZFUhsKUJhX8NFHZmanpDsUmrLefWRmViTVodCczXj3kZlZkVSHQktTxiMFM7Mi6Q4FzymYmY2T8lDIeveRmVmRikJB0i2Stia3xyXdIemlotqaZL1bJe2Q9KWix5ZVmwstOe8+MjMrVlEoRMRfRUR3RHQD24CvAneP1iLiKUmXAxuAK4HXJG0stzYL/SpLS1PGZzSbmRWZ0e4jSSuBZUAX8F5JjySjhhxwLfCNiAhgC3DNNGoTX2eTpB5JPb29vTNp8jiF3UcOBTOzUTOdU/gw8FfADmBjRFwJNAHvBtqBvcl6fRTCo9zaOBGxOSK6IqKrs7Nzhk0+pbD7yHMKZmajKg4FSRngbcBW4MmI2Jfc1QOsBvqBtqTWkbxWubU54TkFM7PxZvIH+BrgJ8lun7skrZOUBd4HPAHspDBXALAO2DWN2pxo9iGpZmbj5Gbw2HcBDybLnwH+ARDw7Yj4QTKS+JykLwDXJ7fdZdbmhA9JNTMbr+JQiIg/Klp+Glg74f6R5Eii9wBfiIhfAJRbmwvefWRmNt5MRgpnFBEDwNcrqc0Ff82Fmdl4qT+jOT8SDOcdDGZmkPpQ8NXXzMyKORRwKJiZjUp3KDRlAfxVF2ZmiXSHwthIwYelmplB6kOhMFLw7iMzs4JUh0Lz6EjBZzWbmQEpDwXvPjIzG8+hgHcfmZmNSncoJEcfnRjySMHMDFIeCh0thW/5OHpiuMYtMTOrD6kOhc6OFgD295+scUvMzOpDqkNhfluO5myGXoeCmRmQ8lCQxOKOZvYfHax1U8zM6kKqQwFgSUeLdx+ZmSUcCh3NHDjmUDAzA4dCYaTg3UdmZoBDgSXntHDg2EkiotZNMTOruWmHgqScpJckbU1uayTdKmmHpC8VrVdxbS4t6WhhKB8cHhiqxcubmdWVSkYKa4G7I6I7IrqBZmADcCXwmqSNki6vtDbzLk3Pko5mwOcqmJkB5Cp4zNXAeyW9DXgKeA74RkSEpC3ADcDhGdR+MPNulW9JcgJb79FBLl06l69sZlZ/Khkp7AA2RsSVQBPQBuxN7usDlgHtM6idRtImST2Senp7eytocmnL5hdCYe+hgVl9XjOzRlRJKDwZEfuS5R6gn0IwAHQkzzmT2mkiYnNEdEVEV2dnZwVNLu2SJR3Mb82x4xd9s/q8ZmaNqJJQuEvSOklZ4H0UPu1vSO5bB+wCds6gNqeyGXHVqsVs/8WBuX5pM7O6U8mcwmeAfwAEfBv4LLBN0heA65PbbuBzFdbm3NWrFnP/M7/klUMDrDi37cwPMDM7S017pBART0fE2ohYExGfjIgRYCOwDbghIn4xk9psdWw6rrpkEQA7dnkXkpmlWyUjhdNExADw9dmqzbXVyzrICF54rb+WzTAzq7nUn9EM0JLLcv7Ceby4/1itm2JmVlMOhcQlS9r5hUPBzFLOoZC4ZEk7u/Yf83cgmVmqORQSqzrbOTaYp/eov+7CzNLLoZC4ZEk7gOcVzCzVHAqJVZ0dADy770iNW2JmVjsOhcTKc9tY1dnOD579Za2bYmZWMw6FItf/2nlsf7GPg8d8JTYzSyeHQpHr33ge+ZHgaztfrnVTzMxqwqFQZM3KBbzjsqX86Zbn2LnbX3lhZunjUCgiic/f9C9YcW4bt/zvR3nt6IlaN8nMbE45FCZY0NbEV373cg4PDPGZ7zxT6+aYmc0ph8IkXr98Ph966yq+++Q+Hnx+dq/0ZmZWzxwKJXzo2tdx0eJ5fOB/PsI3du6pdXPMzOaEQ6GE9pYc3/voNVx23nz+5kc1ucyDmdmccyhMoaMlx293nc+z+47w/C+P1ro5ZmZV51A4g/euXUE2I/5+++5aN8XMrOocCmfQeU4LN11xAXdt381PXjxQ6+aYmVWVQ6EMH7/hMpYvaON3/no77/+b7Wx3OJjZWWraoSBpgaR7Jd0n6ZuSmiW9JGlrcluTrHerpB2SvlT02LJq9WZ+axPf++gGPtx9KS+8doz//H8e5+RwvtbNMjObdZWMFN4PfD4irgNeBT4O3B0R3cntKUmXAxuAK4HXJG0stzYbnaqGc+c184fv+lX+9F+vZd/hE9yzw9+PZGZnn2mHQkR8OSLuT37sBIaB90p6RNIdknLAtcA3onBtyy3ANdOonUbSJkk9knp6e2t7MtmGS5dw5cWL+PP7n/dV2szsrFPxnIKk9cBC4H5gY0RcCTQB7wbagb3Jqn3AsmnUThMRmyOiKyK6Ojs7K23yrJDE7Te+keMn8/yP7/prMMzs7FJRKEhaBHwR+CDwZETsS+7qAVYD/UBbUutIXqfcWt27dOk5bHrrKr79xCs88fKhWjfHzGzWVDLR3Ax8DfhEROwG7pK0TlIWeB/wBLCTwlwBwDpg1zRqDeFD165iUXszn/rW05wY8qSzmZ0dKvlk/vvArwOflLQV+ClwF/A48OOI+AHwI+BNkr5AMhE9jVpDOKe1iT++cQ1Pv3KY/3rPE4yMRK2bZGY2YyrM8VbhiaU24D3AoxHx4nRqU+nq6oqenp6qtLkSX/3hC3zu3p/xnjXLufmaS3jThQtr3SQzs9NI2hkRXWdaL1etBkTEAPD1SmqNZNNbV9F3bJC7tu/mwZ/38tDH38781qZaN8vMrCINMbFbzyTxiXe/nns+tJ6jJ4b5u4d31bpJZmYVcyjMkjcm13f+8tYXeGrP4Vo3x8ysIg6FWfS5G9ewoK2J3/jLH/Gev9jGSweO17pJZmbT4lCYRUvnt/K1f7+ej11/GXsODvC+Lz9Ez66+WjfLzKxsDoVZdv7CedzS/Tq++R/ezIK2Jj7wt4/Qd2yw1s0yMyuLQ6FKVnV28Ne/dznHh/JsfvCMR9qamdUFh0IVXbr0HH5j7QrufHgXew56fsHM6p9Docr+2/W/igQfufsx/u/je6nWyYJmZrPBoVBl5y+cx3//zV/jmVeO8Af/+Dgf/cfH+fuf7ObQcc8zmFn9qdrXXFRLvX3NRblGRoI/u+85vvLDFxgJaM5mWHP+Alae28a/e8vFvH75fFqbsrVuppmdpcr9mguHwhwbyo/w81/2863H9/L4y4d4/pdHOXR8iIzgt7su4BPvfj0L2vw1GWY2u2r+3Uc2uaZshjesmM8bVswH4PDAEN9/ah/PvHKEux95iYde2M9VlyzmmtVLWHv+uaw8t43mnPfymdnc8EihjuzY1cdnv/sMLx8cGDu3QYLl81u5cPE8bum+lGt/pbZXnjOzxuTdRw1sZCR4Ys8hXuw9xkt9x3m57zg7XzrInoMD/Oa6FVy8uJ1FHc0saW9mcUcLFy2ex9JzWpBU66abWZ3y7qMGlsmIN124cNy1GY6eGOLW7zzDg8/38s3H9p72mEXtzSxf0Mrijhbe/LrF/NurL6K9xZvXzKbHI4UGNJQf4eCxQQ4cG2R//0leeK2fZ/cdZX//SfYdPsEz+45w3vxWbvtXb+Qdr19W6+aaWR3wSOEs1pTNsHR+K0vntwJwzerx8ww7dx/kj/7pKX7/zh4uv2ghFyxs45IlHVzS2c6Fi+axuL2Zhe3NtDdnvcvJzMbxSOEsNTg8wld/+AJbn+/l1cMn2Hto4LR1mnMZFs1rZlF74dZ5TguXLu2gtSlLa1OG8xfOo6MlR2tThnnNOZYvaPW5FGYNquEmmiXdAbwB+F5EfLbUeg6FypwYyrPrwDH29A3Qd3yQg8cG6UtuB48XdkW9evgE+w6fmPJ5MoJcJlOY3J7fwrzmHPOas7Q1ZVl6TguL2ptpa84mwVKoL5zXzOKOZlpymbF6NuMRitlcaqjdR5JuBLIRsV7S30paHRE/r3W7ziatTVkuO28+l503f8r1jg8OMzQcHB8a5uW+AY4PDnNiaITjg8PsPTjAyeERBvMjvNjbz6HjQ/QdG+DYyWFODOXZ33+SkTI/YzRlRWtTdixQ2orCZX5bjpXnttGSy5LLiqZshqasCuskj8llM+SyIpcRuUxhuS0JnFxGSCCSf1W4bKooLGeSZYrWyRTdr8IdZCY8btzzjS6TPDZZ16zR1UUoAN3APcnyfcAGwKFQA/Oac9AMC2hi+YK2aT12cHiE/pPDDAzlGRjMc2Ioz8BQngP9Jzl0fIgTQ3lODo9wYmiEE8OFdQYG8xwfyjMwWHjcscFh9h4a4AfPvsZwfqTskKknU4ZMUZhIky+PhgyTBQ+nwieTOf35qtqvqj579V+g2u2fi///m664gJuvWVXV16mXUGgHRo+z7AN+vfhOSZuATQAXXnjh3LbMytacy7Ao1zyrzzkyEgyPBEP5EY4P5jk+OMzxwTzD+WBoZIT8SBSW8yNjIZQfCSIggIjR5eIajEQQFH4YVyt6HEysFT1PlPl8RY/jtNeY8HxFtZEoLDN2/xTPx+i61VPtbK72buyqf7ao+v9/4QWWdLRU94Won1DoB0Y/lnYw4dtbI2IzsBkKcwpz2zSrpUxGNGdEcy6TnHdR/TeFWZrVy5fq7KSwywhgHbCrdk0xM0uvehkpfAvYJmkFcANwdY3bY2aWSnUxUoiIIxQmm7cDb4uIw7VtkZlZOtXLSIGIOMipI5DMzKwG6mKkYGZm9cGhYGZmYxwKZmY2xqFgZmZj6uYL8colqRfYXeHDlwD7Z7E5tXY29eds6gucXf1xX+rXdPpzUUSc8Xq+DRcKMyGpp5xvCWwUZ1N/zqa+wNnVH/elflWjP959ZGZmYxwKZmY2Jm2hsLnWDZhlZ1N/zqa+wNnVH/elfs16f1I1p2BmZlNL20jBzMym4FAwM6tzkhZJeqekJdV+rdSEgqQ7JP1Y0qdq3ZZKSMpJeknS1uS2RtKtknZI+lKt2zcdkpZJ2pYsN0n6jqSHJH2wVK1eTejLSkl7irZRZ1Kv+989SQsk3SvpPknflNQ8WbsbuC/j3jvJeg3x/pG0EPgucCXwgKTOam6bVISCpBuBbESsB1ZJWl3rNlVgLXB3RHRHRDfQTOHCRFcCr0naWMvGlSv5Bb+TwiVYAT4C7IyItwC/JemcErW6M0lfrgJuG91GEdHbQL977wc+HxHXAa8Cv8OEdjdwXz5O0XsnIp6SdDmN8/5ZC/yXiLgN2AK8nSpum1SEAoVrNYx+Lfd9nLrKWyO5GnivpEck3QG8A/hGFI4U2AJcU9PWlS8P3AQcSX7u5tS2eRDoKlGrRxP7cjVws6RHJd2e1LppgN+9iPhyRNyf/NgJ/C6nt7t7klrdmaQvwxS9dyTlgGtpkPdPRPwwIrZLeiuFEHsXVdw2aQmFdmBvstwHLKthWyq1A9gYEVcCTRSuad1wfYqIIxMuojTZtmmI7TVJX+6l8Oa8AlgvaS0N0pdRktYDC4GXadDtMqqoL/cz/r3zbhqvL6LwAeQgEFRx26QlFPop/BEF6KAx+/1kROxLlns4O/oEk/ejUfv2cEQcjYg88Biwmgbqi6RFwBeBD9Lg22VCXya+dxpquwBEwYeBJ4E3U8VtU9f/EbNoJ6eGU+uAXbVrSsXukrROUhZ4H4VPBo3eJ5h82zTq9toiabmkecB1wNM0SF8kNQNfAz4REbtp4O0ySV8mvneeoEH6AiDpY5J+L/nxXOCPqea2iYiz/gbMp/CL8HngWWBBrdtUQR/eSOFTwlPAbRQC/SHgC8BzwCW1buM0+7M1+fci4KdJP3YA2clqtW5vmX15G/CzZDv9x6TWEL97wC0Udk1sTW4fmNjuBu7Lp4vfO8k6DfP+4dQusAeBLyfbomrbJjVnNCdHirwTeDAiXq11e2aDpDbgPcCjEfFirdtTKUkrKHzK2RLJPvrJao2qUX/3Jmt3o/ZlMo38/qnmtklNKJiZ2ZmlZU7BzMzK4FAwM7MxDgUzMxvjUDAzszEOBTMzG/P/ASLQV33wGf2QAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#不同类型的新闻出现的次数\n",
    "plt.plot(user_click_merge['category_id'].value_counts().values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2339cd90438>]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#出现次数比较少的新闻类型, 有些新闻类型，基本上就出现过几次\n",
    "plt.plot(user_click_merge['category_id'].value_counts().values[150:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1.630633e+06\n",
       "mean     2.043012e+02\n",
       "std      6.382198e+01\n",
       "min      0.000000e+00\n",
       "25%      1.720000e+02\n",
       "50%      1.970000e+02\n",
       "75%      2.290000e+02\n",
       "max      6.690000e+03\n",
       "Name: words_count, dtype: float64"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#新闻字数的描述性统计\n",
    "user_click_merge['words_count'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x233e7c39c50>]"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(user_click_merge['words_count'].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 用户点击的新闻类型的偏好\n",
    "\n",
    "此特征可以用于度量用户的兴趣是否广泛。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2339cc1ee48>]"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(sorted(user_click_merge.groupby('user_id')['category_id'].nunique(), reverse=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上图中可以看出有一小部分用户阅读类型是极其广泛的，大部分人都处在20个新闻类型以下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>category_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>250000.000000</td>\n",
       "      <td>250000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>124999.500000</td>\n",
       "      <td>4.573188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>72168.927986</td>\n",
       "      <td>4.419800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>62499.750000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>124999.500000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>187499.250000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>249999.000000</td>\n",
       "      <td>95.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             user_id    category_id\n",
       "count  250000.000000  250000.000000\n",
       "mean   124999.500000       4.573188\n",
       "std     72168.927986       4.419800\n",
       "min         0.000000       1.000000\n",
       "25%     62499.750000       2.000000\n",
       "50%    124999.500000       3.000000\n",
       "75%    187499.250000       6.000000\n",
       "max    249999.000000      95.000000"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_click_merge.groupby('user_id')['category_id'].nunique().reset_index().describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 用户查看文章的长度的分布\n",
    "\n",
    "通过统计不同用户点击新闻的平均字数，这个可以反映用户是对长文更感兴趣还是对短文更感兴趣。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x233e7b66978>]"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(sorted(user_click_merge.groupby('user_id')['words_count'].mean(), reverse=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上图中可以发现有一小部分人看的文章平均词数非常高，也有一小部分人看的平均文章次数非常低。\n",
    "\n",
    "大多数人偏好于阅读字数在200-400字之间的新闻。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x23444758208>]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#挑出大多数人的区间仔细看看\n",
    "plt.plot(sorted(user_click_merge.groupby('user_id')['words_count'].mean(), reverse=True)[1000:45000])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以发现大多数人都是看250字以下的文章"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>words_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>250000.000000</td>\n",
       "      <td>250000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>124999.500000</td>\n",
       "      <td>205.830189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>72168.927986</td>\n",
       "      <td>47.174030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>62499.750000</td>\n",
       "      <td>187.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>124999.500000</td>\n",
       "      <td>202.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>187499.250000</td>\n",
       "      <td>217.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>249999.000000</td>\n",
       "      <td>3434.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             user_id    words_count\n",
       "count  250000.000000  250000.000000\n",
       "mean   124999.500000     205.830189\n",
       "std     72168.927986      47.174030\n",
       "min         0.000000       8.000000\n",
       "25%     62499.750000     187.500000\n",
       "50%    124999.500000     202.000000\n",
       "75%    187499.250000     217.750000\n",
       "max    249999.000000    3434.500000"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#更加详细的参数\n",
    "user_click_merge.groupby('user_id')['words_count'].mean().reset_index().describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 用户点击新闻的时间分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "#为了更好的可视化，这里把时间进行归一化操作\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "mm = MinMaxScaler()\n",
    "user_click_merge['click_timestamp'] = mm.fit_transform(user_click_merge[['click_timestamp']])\n",
    "user_click_merge['created_at_ts'] = mm.fit_transform(user_click_merge[['created_at_ts']])\n",
    "\n",
    "user_click_merge = user_click_merge.sort_values('click_timestamp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>click_article_id</th>\n",
       "      <th>click_timestamp</th>\n",
       "      <th>click_environment</th>\n",
       "      <th>click_deviceGroup</th>\n",
       "      <th>click_os</th>\n",
       "      <th>click_country</th>\n",
       "      <th>click_region</th>\n",
       "      <th>click_referrer_type</th>\n",
       "      <th>category_id</th>\n",
       "      <th>created_at_ts</th>\n",
       "      <th>words_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>249990</td>\n",
       "      <td>162300</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "      <td>0.989186</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>249998</td>\n",
       "      <td>160974</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "      <td>0.989092</td>\n",
       "      <td>259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>249985</td>\n",
       "      <td>160974</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "      <td>0.989092</td>\n",
       "      <td>259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>249979</td>\n",
       "      <td>162300</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "      <td>0.989186</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>249988</td>\n",
       "      <td>160974</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "      <td>0.989092</td>\n",
       "      <td>259</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    user_id  click_article_id  click_timestamp  click_environment  \\\n",
       "18   249990            162300         0.000000                  4   \n",
       "2    249998            160974         0.000002                  4   \n",
       "30   249985            160974         0.000003                  4   \n",
       "50   249979            162300         0.000004                  4   \n",
       "25   249988            160974         0.000004                  4   \n",
       "\n",
       "    click_deviceGroup  click_os  click_country  click_region  \\\n",
       "18                  3        20              1            25   \n",
       "2                   1        12              1            13   \n",
       "30                  1        17              1             8   \n",
       "50                  1        17              1            25   \n",
       "25                  1        17              1            21   \n",
       "\n",
       "    click_referrer_type  category_id  created_at_ts  words_count  \n",
       "18                    2          281       0.989186          193  \n",
       "2                     2          281       0.989092          259  \n",
       "30                    2          281       0.989092          259  \n",
       "50                    2          281       0.989186          193  \n",
       "25                    2          281       0.989092          259  "
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_click_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mean_diff_time_func(df, col):\n",
    "    df = pd.DataFrame(df, columns={col})\n",
    "    df['time_shift1'] = df[col].shift(1).fillna(0)\n",
    "    df['diff_time'] = abs(df[col] - df['time_shift1'])\n",
    "    return df['diff_time'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 点击时间差的平均值\n",
    "mean_diff_click_time = user_click_merge.groupby('user_id')['click_timestamp', 'created_at_ts'].apply(lambda x: mean_diff_time_func(x, 'click_timestamp'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x233a1470e48>]"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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x79dN4mhrO4+9tYOGo61894bJCnyRCKWwD2M+n/H9m6eSHBfNL5fvprL+KA/fOo10nZMvEnE0Zx/mfD7j29dM5IFrJ/L21hqu/NEylm6t9rosERlgCvsIYGZ85sJRPP/FC0hLiOGTv17Df7ywiaOt7V6XJiIDRGEfQSblpvDClxZw7wUj+c2KPVz/6DtsqjjjOvAiEiYU9hEmLiaKf79+Er/79Bzqj7Ry809X8NSKPV6XJSL9TGEfoS4cm8mrX72IBWMz+M4Lm3QBlkiYU9hHsPTEWH75j7O4dlrnBVj//Md1NLW0eV2WiPQDhX2Ei/IZj945k29cOZ6XNlRww2Pv8NaWajo6NMoXCSc6z17w+YwvLhrDzOGpfOPPG/jUb9aQnxbPjTNyuXP2cArSE7wuUUR6SXe9lA9pbe/g5Y2VPPteOe9sr8HMuHlmHl+5dKxCX2QQ0i2Opdcq64/wy2W7+f3qUnDwifmFfO7i0WQkDfG6NBEJUNhLn6msP8Ijr2/jmffKiIuO4uPzhnPvgpHk+OO9Lk0k4inspc/tqG7ip2/t4C/ryon2+fjE/EK+ctk4kobo0I+IV7R4ifS5MVlJ/PCOGbz9jUXcOCOXX72zm2t/spyNZboKV2SwU9jLWStIT+D/fmw6f7qviJbWDm786Tvc/9xGKuqOeF2aiHRDYS/nbM7IdF776kV8fF4hi4v3sfD/LeU7f/mA6oajXpcmIqfRnL30ibJDh3nszR08s7YMn8+4esowbpyRy4IxmcRGa0wh0l90gFY8UVrbzK+W7+aF9RXUH2klNSGGq6cM47bz8zlveJpWyhLpYwp78dSxtg6Wb6/hhfUVLCmp4vCxdkZlJHLjjDxuPT+P/DRdoCXSFxT2Mmg0t7Tx0oZKnn2vjNW7D+IzuHpKDnfNGc7cUenERGmaR+RcKexlUCqvO8JvV+7h6dV7aTzaRmpCDJeMz+KicZlcNilb5+yLnKU+DXszexKYBLzknHswmDZmFg3sCjwAvuyc29jd91DYR5Yjx9p5e1sNr35QybLtBzjYfIykIdHcU1TIFxaOJjkuxusSRUJCsGHf4zDKzG4BopxzRWb2X2Y21jm3vac2QDLw3865fznXTkj4io+N4qopw7hqyjA6Ohzv7T3Eb1bs4edv7+SZtWV87bJx3HJeHnExUV6XKhIWehzZm9lPgFedcy+b2Z1AvHPu1z21CTy+CDQDG4HPOefaTtvvPuA+gOHDh59fWlraR92SULV+Xx3ffXET7+2tIz4miovHZXLF5GwumZBFakKs1+WJDDp9NrIHEoHywPODwHlBtnkDuMw5V2lmvwWuAV44dSfn3BPAE9A5jRNELRLmphek8uzn57NyVy0vb6xkSUkVr27aT5TPmDsynUXjs7hwXAbjs5N1GqfIWQgm7JvoHKUDJNH1VbddtdngnGsJbCsGxvaiTokgZsb80RnMH53B926YwobyepaU7Of1TVU89PJmeBmyU4Zw4dhMLhqXyYVjMkhL1Khf5EyCCfu1wAJgFTAd2Bpkm9+Z2UPAB8BNwPf7omCJLD6fMaMglRkFqXzjyglU1B1h+fYalm07wJKSKp5ZW4YZTMvzc83UHG6fVaDgF+lCMHP2KcByOqdlrgbuBD7mnHvgDG3mAQXA04ABLzjn7j/T99HZOHK22jsc68vqWLathqVba1i3r45on3HF5Gw+Pq+QolFDNdUjYa+vT71MAy4Hljnn9p9rmzNR2EtvbdnfwJ+Ly3j2vTLqDrdSkB7PpROyuXRiFnNGpjMkWmf2SPjRRVUSsY62tvPi+gpe+WA/7+44QEtbB4mxUVw0LpNLJmSxaEKWllaUsKGwF6Hz4q0VOw/wxpZq3txczf6Go51z/PmpXDgmgwvGZHBeYapG/RKyFPYip3HOsamigTe3VPPW1mo2lNXT3uGIi/GxaHwWt52fz4VjdUtmCS0Ke5EeNB5tZfWugyzbXsNfN1SeuGXDReMyuGRCNgvHZ2q6RwY9hb3IWTjW1sE7O2pYUlLNm1uqqGpowQym56dy6YQszh+RxuQcP/4E3bNHBheFvcg5OnW6540t1azfV3fi7/LT4pkwLJnxw5KZnOtnRkEquanxZ3g1kf6lsBfpI7VNLWwsr2dTRQMllQ1sr2pkV00zbR2d750cfxxzR6Yzf3QGRaOHUpCuhVlk4PTlvXFEItrQpCEsHJ/FwvFZJ7a1tLWzpbKRdfvqWLPnIO/sqOX5dRVA5+i/aNRQ5o8ZStGoDIb547wqXeQEjexF+oBzjh3VTazYWcvKnbWs3FVL/ZFWAMZmJXH11BwuHpfJtHy/VuaSPqVpHBEPdXQ4SiobWLmzlje2VLF690Gcg8TYKGaPTOfSidlcNjGLHL/m+6V3FPYig8jB5mOs2lXLql21LNtWw57awwBMz/ezYGwGc0cO5fzCNBK1LKOcJYW9yCDlnGNnTROvl1SxpKTqxMVdUT5jer6fotFDmTUinfOGp+GP16mecmYKe5EQ0dzSxtrSQ6zeXcu7O2rZWN4Z/j6DmcPTWDguk/ljMjTfL11S2IuEqOaWNtbvq2PVrlqWbqthY3k9zkFCbBSTclKYlJvCtPxUpuX7GZ2ZRJRPt3GOZAp7kTBxqPkYKwPz/ZsrGyipaKD5WDvQecB3cp6faXl+phWkMi3PT+HQBN3HP4Io7EXCVEeHY9eBJtbvq2djeT3ry+ooqWigpa0DAH98DNPy/UzN8zMtP5XpBX6GpcTpAyBMKexFIkhrewfbqhrZUFYfeNSxdX/jiat8M5OHMKMglfML05gwLJnRmUnkpcbj0xRQyNMVtCIRJCbKx+RcP5Nz/dw1p3Pb0dZ2Nlc2sKGsnvX76nhv7yGWlFSd2Cc22kdBWjz5aQmMGJrAqMwkRmUmMioziZyUOH0QhBmFvUiYiouJYubwNGYOTzux7VDzMbZXN7GzpondB5rZW3uYsrrDrC09RFNL2yn7+piWl8qiCVnMHpHGlDw/cTFa4CWUKexFIkhaYixzRqYzZ2T6h7Y756hpbGFnTTO7DjSxs7qZlbtqefjVLQBE+4yx2clMzUthan4qM/JTmZCTrFNBQ4jCXkQwM7JS4shKiaNo9NAT22saW1i3r4739x7ig4oG/ra5msXFZQDEx0QxvcDPrMJ0zh+RxqzCNJLjdBHYYKUDtCISNOcc5XVHeH9vHWtLD7G29BAllQ20dzjMYGRGIlNy/UzOTWFqnp8JOSmkJ8Z6XXZY0wFaEelzZkZ+WgL5aQlcPz0X6LwIbN2+zvD/oLye4j0HeWF9xYl9MpJiGZOVxLjsZCbnpjC9IJXRmUmaAhpgGtmLSJ872HyMD8rr2VbVyLaqRnZUN7GtqunEQeDYKB9jspKYMCyZqfmdK35NzEnRQeBzoPPsRWRQ6ehw7KltZn1ZHVsqGympbGDL/kZqGlsA8BkMT09gwrAUpuZ3TgVNyfNr0fceaBpHRAYVn88C5/InwcyT2yvrO48BbKlsYHt1E5srG3h10/4Tf5+RFMvEnBTGZ3f+L2BKnp8RQxN1T6CzpLAXEU/l+OPJmRrPNVNzTmyrP9JKSUUDmyo6p4JKKhv43arSE7eEGBLtY2RGIuMDi79PGJbMhGEp5Ph1W4juKOxFZNDxx8dQNHroh04DbWvvYFtVE5sq6tle3cT2qkbW7D7IX9adPBicnhjL+OxkJuWmMCknhYk5KYzJSiI2WgeDFfYiEhKio3ydIZ6b8qHt9UdaO0f/FQ1sDhwH+MPqUo62dv4vICbKGJv14Q+ASTkp+BMi65oAhb2IhDR/fAyzR6Qze8TJq4LbOxy7DzRTErgldEllA0u31vDM2rITbfJS4z/0ATA5N4X8tPiwnQZS2ItI2InyGWOykhiTlcQNgesBAKobj7K5svHEB0BJRT1/21zF8ZMSk+OiT4z8jy8UMzY7iSHRoX9KqMJeRCJGVnIcWclxXDwu88S2w8fa2Lq/sfNDoLKekooG/rRmH0daOxeIifYZk3JTmFmQyszhaZxfmBaS/wPQefYiIqdp73CU1nZOA22qaGDd3jrWl9VxOLBCWF5qPBeNy+DCsZnMHz2U1ATvbgmhi6pERPpQW3sHW6saWVt6iHe2H2DlzloaW9rwGUzLT+XCsZ3hP3N46oDeCkJhLyLSj9raO1hfVseybQdYvr2Gdfvq6HCQNCSaeaOGcsWkbC6flE1aP98ITmEvIjKA6o+0snJnLcu31/D2thrKDh0h2mdcNC6Tm2bmccWk7H65949ulyAiMoD88TFcNWUYV00ZhnOOjeX1vLSxkhfWVfDmlmrSEmL42KwC7plXSEF6woDXF9TI3syeBCYBLznnHgy2TTD7HaeRvYiEo44Ox4qdtfxhdSmvl1ThnOPqqTn88yVjGT8sudev32cjezO7BYhyzhWZ2X+Z2Vjn3Pae2gBTe9pPRCTc+XzGgrEZLBibQWX9EZ5aUcrvV5Xy8sZKrp4yjK9cOq5PQr/HOoJosxBYHHj+OrAgyDbB7CciEjFy/PH869UTWP7NRXxx4RiWbTvAlT9axvdf3tzv3zuYsE8EygPPDwLZQbbpcT8zu8/Mis2suKam5mzqFhEJWWmJsXz9yvEs/+Yi/rGokBFDE/v9ewZzgLYJiA88T6LrD4iu2vS4n3PuCeAJ6JyzD7pqEZEwkJYYy/dunDIg3yuYkf1aTk7BTAf2BNkmmP1ERGQABDOyfx5Ybma5wNXAnWb2oHPugTO0mQe4LraJiIgHehzZO+ca6DzYugpY5Jxbf1rQd9WmvqttfVu6iIgEK6iLqpxzhzh5Zk3QbYLZT0RE+p/W6hIRiQAKexGRCKCwFxGJAAp7EZEIMGhucWxmNUBpL14iAzjQR+WEgkjrL6jPkUJ9PjuFzrnMnhoNmrDvLTMrDubOb+Ei0voL6nOkUJ/7h6ZxREQigMJeRCQChFPYP+F1AQMs0voL6nOkUJ/7QdjM2YuISPfCaWQvIiLdUNiLiESAkA97M3vSzFaa2QM9tx68zCzazPaa2dLAY6qZfdfM1pjZT09pd87bBhMzyzaz5YHnMWb2opm9a2b39se2weC0PueZWdkpP+/MwPaP/D73ZptXzMxvZq+Y2etm9pyZxfZ13wZTf6HbPn/oPR1o58n7OqTD3k5Z6BwYFVjoPFRNA/7bObfQObcQiKVz8Zc5QLWZXWZm55/rNg/60y0zSwOeonPpSoAvA2udcxcAt5lZcj9s81QXfZ4LPHT85+2cq+nq97k32wa+lx9yN/CIc+4KYD9wJ33Yt0HYX/hon/+VU97TzrmNvXkP9/Z9HdJhT3gtaj4PuM7M/m5mTwKXAs+6ziPorwEXAhf3Yttg0g7cATQEvl7IyZ/jMmBWP2zz2ul9ngd8xszeM7PvB7Yt5KO/z73Z5hnn3OPOuSWBLzOBj9O3fetqm6e66HMbp7ynzSya3r2He/W+DvWwD2Yx9FCxBrjMOTcHiKFz/d5gFnE/p8XeveScazhtMZve9Csk+t9Fn1+hM7BmA0VmNo0w6zOAmRUBacA+wvxnfNwpfV7Ch9/T1+Bhn0M97INZDD1UbHDOVQaeFxP8Iu7ntNj7INPXfQ2F/q9wzjU659qB94GxhFmfzSwdeBS4lwj5GZ/W59Pf057+jAfFP1AvhNOi5r8zs+lmFgXcROeneDCLuIfDYu+96Veo9v81M8sxswTgCuADwqjPZhYL/Bn4lnOulAj4GXfR59Pf0+vxss/OuZB9ACmBf8BHgM2A3+uaetGXKcAGYCPwEJ0fxO8CPwa2AiN7s83r/nXT56WBPwuBTYF61wBRfb3N67520edFwJbAz/xL3f0+92abx/38PHAIWBp4fKIv+zbY+ttNn79z6ns60Maz97Xnv/x98A+cBtwODPO6ln7oWzxwGzCqL7YN5geQG/g5+vtrWyg8uvp97s22wfTo674N9v6e4d/Bk/e1bpcgIhIBQn3OXkREgqCwFxGJAAp7EZEIoLAXEYkACnsRkQjw/wGzGHr2qPr+8QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(sorted(mean_diff_click_time.values, reverse=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上图可以发现不同用户点击文章的时间差是有差异的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 前后点击文章的创建时间差的平均值\n",
    "mean_diff_created_time = user_click_merge.groupby('user_id')['click_timestamp', 'created_at_ts'].apply(lambda x: mean_diff_time_func(x, 'created_at_ts'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2343edf2780>]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(sorted(mean_diff_created_time.values, reverse=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从图中可以发现用户先后点击文章，文章的创建时间也是有差异的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 用户前后点击文章的相似性分布\n",
    "item_idx_2_rawid_dict = dict(zip(item_emb_df['article_id'], item_emb_df.index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "del item_emb_df['article_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [],
   "source": [
    "item_emb_np = np.ascontiguousarray(item_emb_df.values, dtype=np.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>click_article_id</th>\n",
       "      <th>click_timestamp</th>\n",
       "      <th>click_environment</th>\n",
       "      <th>click_deviceGroup</th>\n",
       "      <th>click_os</th>\n",
       "      <th>click_country</th>\n",
       "      <th>click_region</th>\n",
       "      <th>click_referrer_type</th>\n",
       "      <th>category_id</th>\n",
       "      <th>created_at_ts</th>\n",
       "      <th>words_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>84588</th>\n",
       "      <td>218464</td>\n",
       "      <td>199198</td>\n",
       "      <td>0.007031</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>323</td>\n",
       "      <td>0.989226</td>\n",
       "      <td>221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84589</th>\n",
       "      <td>218464</td>\n",
       "      <td>162655</td>\n",
       "      <td>0.007039</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "      <td>281</td>\n",
       "      <td>0.989199</td>\n",
       "      <td>245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113519</th>\n",
       "      <td>207860</td>\n",
       "      <td>272143</td>\n",
       "      <td>0.010669</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>399</td>\n",
       "      <td>0.989235</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113520</th>\n",
       "      <td>207860</td>\n",
       "      <td>271045</td>\n",
       "      <td>0.010677</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>399</td>\n",
       "      <td>0.989278</td>\n",
       "      <td>262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135951</th>\n",
       "      <td>200605</td>\n",
       "      <td>272143</td>\n",
       "      <td>0.019109</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>399</td>\n",
       "      <td>0.989235</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        user_id  click_article_id  click_timestamp  click_environment  \\\n",
       "84588    218464            199198         0.007031                  4   \n",
       "84589    218464            162655         0.007039                  4   \n",
       "113519   207860            272143         0.010669                  4   \n",
       "113520   207860            271045         0.010677                  4   \n",
       "135951   200605            272143         0.019109                  4   \n",
       "\n",
       "        click_deviceGroup  click_os  click_country  click_region  \\\n",
       "84588                   3        20              1            21   \n",
       "84589                   3        20              1            21   \n",
       "113519                  1        12              1            20   \n",
       "113520                  1        12              1            20   \n",
       "135951                  3         2             10            28   \n",
       "\n",
       "        click_referrer_type  category_id  created_at_ts  words_count  \n",
       "84588                     2          323       0.989226          221  \n",
       "84589                     2          281       0.989199          245  \n",
       "113519                    1          399       0.989235          184  \n",
       "113520                    1          399       0.989278          262  \n",
       "135951                    2          399       0.989235          184  "
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 随机选择5个用户，查看这些用户前后查看文章的相似性\n",
    "sub_user_ids = np.random.choice(user_click_merge.user_id.unique(), size=15, replace=False)\n",
    "sub_user_info = user_click_merge[user_click_merge['user_id'].isin(sub_user_ids)]\n",
    "\n",
    "sub_user_info.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_item_sim_list(df):\n",
    "    sim_list = []\n",
    "    item_list = df['click_article_id'].values\n",
    "    for i in range(0, len(item_list)-1):\n",
    "        emb1 = item_emb_np[item_idx_2_rawid_dict[item_list[i]]]\n",
    "        emb2 = item_emb_np[item_idx_2_rawid_dict[item_list[i+1]]]\n",
    "        sim_list.append(np.dot(emb1,emb2)/(np.linalg.norm(emb1)*(np.linalg.norm(emb2))))\n",
    "    sim_list.append(0)\n",
    "    return sim_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
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     "output_type": "display_data"
    }
   ],
   "source": [
    "for _, user_df in sub_user_info.groupby('user_id'):\n",
    "    item_sim_list = get_item_sim_list(user_df)\n",
    "    plt.plot(item_sim_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从图中可以看出有些用户前后看的商品的相似度波动比较大，有些波动比较小，也是有一定的区分度的"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 总结\n",
    "\n",
    "通过数据分析的过程， 我们目前可以得到以下几点重要的信息， 这个对于我们进行后面的特征制作和分析非常有帮助：\n",
    "1. 训练集和测试集的用户id没有重复，也就是测试集里面的用户没有模型是没有见过的\n",
    "2. 训练集中用户最少的点击文章数是2， 而测试集里面用户最少的点击文章数是1\n",
    "3. 用户对于文章存在重复点击的情况， 但这个都存在于训练集里面\n",
    "4. 同一用户的点击环境存在不唯一的情况，后面做这部分特征的时候可以采用统计特征\n",
    "5. 用户点击文章的次数有很大的区分度，后面可以根据这个制作衡量用户活跃度的特征\n",
    "6. 文章被用户点击的次数也有很大的区分度，后面可以根据这个制作衡量文章热度的特征\n",
    "7. 用户看的新闻，相关性是比较强的，所以往往我们判断用户是否对某篇文章感兴趣的时候， 在很大程度上会和他历史点击过的文章有关\n",
    "8. 用户点击的文章字数有比较大的区别， 这个可以反映用户对于文章字数的区别\n",
    "9. 用户点击过的文章主题也有很大的区别， 这个可以反映用户的主题偏好\n",
    "10.不同用户点击文章的时间差也会有所区别， 这个可以反映用户对于文章时效性的偏好\n",
    "\n",
    "所以根据上面的一些分析，可以更好的帮助我们后面做好特征工程， 充分挖掘数据的隐含信息。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "关于Datawhale： Datawhale是一个专注于数据科学与AI领域的开源组织，汇集了众多领域院校和知名企业的优秀学习者，聚合了一群有开源精神和探索精神的团队成员。Datawhale 以“for the learner，和学习者一起成长”为愿景，鼓励真实地展现自我、开放包容、互信互助、敢于试错和勇于担当。同时 Datawhale 用开源的理念去探索开源内容、开源学习和开源方案，赋能人才培养，助力人才成长，建立起人与人，人与知识，人与企业和人与未来的联结。 本次数据挖掘路径学习，专题知识将在天池分享，详情可关注Datawhale：\n",
    "\n",
    "![image-20201119112159065](http://ryluo.oss-cn-chengdu.aliyuncs.com/abc/image-20201119112159065.png)"
   ]
  }
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